{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "is_executing": false
    }
   },
   "source": [
    "3.11 模型选择、欠拟合和过拟合\n",
    "在前几节基于Fashion-MNIST数据集的实验中，我们评价了机器学习模型在训练数据集和测试数据集上的表现。如果你改变过实验中的模型结构或者超参数，你也许发现了：当模型在训练数据集上更准确时，它在测试数据集上却不一定更准确。这是为什么呢？\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.1 训练误差和泛化误差\n",
    "在解释上述现象之前，我们需要区分训练误差（training error）和泛化误差（generalization error）。通俗来讲，前者指模型在训练数据集上表现出的误差，后者指模型在任意一个测试数据样本上表现出的误差的期望，并常常通过测试数据集上的误差来近似。计算训练误差和泛化误差可以使用之前介绍过的损失函数，例如线性回归用到的平方损失函数和softmax回归用到的交叉熵损失函数。\n",
    "\n",
    "让我们以高考为例来直观地解释训练误差和泛化误差这两个概念。训练误差可以认为是做往年高考试题（训练题）时的错误率，泛化误差则可以通过真正参加高考（测试题）时的答题错误率来近似。假设训练题和测试题都随机采样于一个未知的依照相同考纲的巨大试题库。如果让一名未学习中学知识的小学生去答题，那么测试题和训练题的答题错误率可能很相近。但如果换成一名反复练习训练题的高三备考生答题，即使在训练题上做到了错误率为0，也不代表真实的高考成绩会如此。\n",
    "\n",
    "在机器学习里，我们通常假设训练数据集（训练题）和测试数据集（测试题）里的每一个样本都是从同一个概率分布中相互独立地生成的。基于该独立同分布假设，给定任意一个机器学习模型（含参数），它的训练误差的期望和泛化误差都是一样的。例如，如果我们将模型参数设成随机值（小学生），那么训练误差和泛化误差会非常相近。但我们从前面几节中已经了解到，模型的参数是通过在训练数据集上训练模型而学习出的，参数的选择依据了最小化训练误差（高三备考生）。所以，训练误差的期望小于或等于泛化误差。也就是说，一般情况下，由训练数据集学到的模型参数会使模型在训练数据集上的表现优于或等于在测试数据集上的表现。由于无法从训练误差估计泛化误差，一味地降低训练误差并不意味着泛化误差一定会降低。\n",
    "\n",
    "机器学习模型应关注降低泛化误差。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.2 模型选择\n",
    "在机器学习中，通常需要评估若干候选模型的表现并从中选择模型。这一过程称为模型选择（model selection）。可供选择的候选模型可以是有着不同超参数的同类模型。以多层感知机为例，我们可以选择隐藏层的个数，以及每个隐藏层中隐藏单元个数和激活函数。为了得到有效的模型，我们通常要在模型选择上下一番功夫。下面，我们来描述模型选择中经常使用的验证数据集（validation data set）。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.2.1 验证数据集\n",
    "从严格意义上讲，测试集只能在所有超参数和模型参数选定后使用一次。不可以使用测试数据选择模型，如调参。由于无法从训练误差估计泛化误差，因此也不应只依赖训练数据选择模型。鉴于此，我们可以预留一部分在训练数据集和测试数据集以外的数据来进行模型选择。这部分数据被称为验证数据集，简称验证集（validation set）。例如，我们可以从给定的训练集中随机选取一小部分作为验证集，而将剩余部分作为真正的训练集。\n",
    "\n",
    "然而在实际应用中，由于数据不容易获取，测试数据极少只使用一次就丢弃。因此，实践中验证数据集和测试数据集的界限可能比较模糊。从严格意义上讲，除非明确说明，否则本书中实验所使用的测试集应为验证集，实验报告的测试结果（如测试准确率）应为验证结果（如验证准确率）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.2.3 K折交叉验证\n",
    "由于验证数据集不参与模型训练，当训练数据不够用时，预留大量的验证数据显得太奢侈。一种改善的方法是K折交叉验证（K-fold cross-validation）。在K折交叉验证中，我们把原始训练数据集分割成K个不重合的子数据集，然后我们做K次模型训练和验证。每一次，我们使用一个子数据集验证模型，并使用其他K−1个子数据集来训练模型。在这K次训练和验证中，每次用来验证模型的子数据集都不同。最后，我们对这K次训练误差和验证误差分别求平均。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.3 欠拟合和过拟合\n",
    "接下来，我们将探究模型训练中经常出现的两类典型问题：一类是模型无法得到较低的训练误差，我们将这一现象称作欠拟合（underfitting）；另一类是模型的训练误差远小于它在测试数据集上的误差，我们称该现象为过拟合（overfitting）。在实践中，我们要尽可能同时应对欠拟合和过拟合。虽然有很多因素可能导致这两种拟合问题，在这里我们重点讨论两个因素：模型复杂度和训练数据集大小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.3.1 模型复杂度\n",
    "为了解释模型复杂度，我们以多项式函数拟合为例。给定一个由标量数据特征x和对应的标量标签y组成的训练数据集，多项式函数拟合的目标是找一个K阶多项式函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了解释模型复杂度，我们以多项式函数拟合为例。给定一个由标量数据特征 x 和对应的标量标签 y 组成的训练数据集，多项式函数拟合的目标是找一个 K 阶多项式函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\hat{y} = b + \\sum_{k=1}^K x^k w_k\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "来近似 y。在上式中，wk是模型的权重参数，b是偏差参数。与线性回归相同，多项式函数拟合也使用平方损失函数。特别地，一阶多项式函数拟合又叫线性函数拟合。\n",
    "\n",
    "因为高阶多项式函数模型参数更多，模型函数的选择空间更大，所以高阶多项式函数比低阶多项式函数的复杂度更高。因此，高阶多项式函数比低阶多项式函数更容易在相同的训练数据集上得到更低的训练误差。给定训练数据集，模型复杂度和误差之间的关系通常如图3.4所示。给定训练数据集，如果模型的复杂度过低，很容易出现欠拟合；如果模型复杂度过高，很容易出现过拟合。应对欠拟合和过拟合的一个办法是针对数据集选择合适复杂度的模型。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.3.2 训练数据集大小\n",
    "影响欠拟合和过拟合的另一个重要因素是训练数据集的大小。一般来说，如果训练数据集中样本数过少，特别是比模型参数数量（按元素计）更少时，过拟合更容易发生。此外，泛化误差不会随训练数据集里样本数量增加而增大。因此，在计算资源允许的范围之内，我们通常希望训练数据集大一些，特别是在模型复杂度较高时，例如层数较多的深度学习模型。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.4 多项式函数拟合实验\n",
    
    "为了理解模型复杂度和训练数据集大小对欠拟合和过拟合的影响，下面我们以多项式函数拟合为例来实验。首先导入实验需要的包或模块。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "from tensorflow.keras.layers import Conv2D,BatchNormalization,Activation\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "import d2lzh as d2l\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.4.1 生成数据集\n",
    "我们将生成一个人工数据集。在训练数据集和测试数据集中，给定样本特征x，我们使用如下的三阶多项式函数来生成该样本的标签：y = 1.2x - 3.4x^2 + 5.6x^3 + 5 + epsilon 其中噪声项ϵ服从均值为0、标准差为0.01的正态分布。训练数据集和测试数据集的样本数都设为100。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 3)\n",
      "tf.Tensor([200], shape=(1,), dtype=int32)\n",
      "tf.Tensor([200], shape=(1,), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "n_train, n_test, true_w, true_b = 100, 100, [1.2, -3.4, 5.6], 5\n",
    "features = tf.random.normal(shape=(n_train + n_test, 1))\n",
    "poly_features = tf.concat([features, tf.pow(features, 2), tf.pow(features, 3)],1)\n",
    "print(poly_features.shape)\n",
    "labels = (true_w[0] * poly_features[:, 0] + true_w[1] * poly_features[:, 1]+ true_w[2] * poly_features[:, 2] + true_b)\n",
    "print(tf.shape(labels))\n",
    "# labels += tf.random.normal(labels.shape,0,0.1)\n",
    "print(tf.shape(labels))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "看一看生成的数据集的前两个样本。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<tf.Tensor: id=2713209, shape=(2, 1), dtype=float32, numpy=\n",
       " array([[-1.9730895 ],\n",
       "        [ 0.37837178]], dtype=float32)>,\n",
       " <tf.Tensor: id=2713213, shape=(2, 3), dtype=float32, numpy=\n",
       " array([[-1.9730895 ,  3.893082  , -7.681399  ],\n",
       "        [ 0.37837178,  0.14316519,  0.05416967]], dtype=float32)>,\n",
       " <tf.Tensor: id=2713217, shape=(2,), dtype=float32, numpy=array([-53.62002  ,   5.2706347], dtype=float32)>)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features[:2], poly_features[:2], labels[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.4.2. 定义、训练和测试模型¶\n",
    "我们先定义作图函数semilogy，其中 y 轴使用了对数尺度。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def semilogy(x_vals, y_vals, x_label, y_label, x2_vals=None, y2_vals=None,\n",
    "             legend=None, figsize=(3.5, 2.5)):\n",
    "    d2l.set_figsize(figsize)\n",
    "    d2l.plt.xlabel(x_label)\n",
    "    d2l.plt.ylabel(y_label)\n",
    "    d2l.plt.semilogy(x_vals, y_vals)\n",
    "    if x2_vals and y2_vals:\n",
    "        d2l.plt.semilogy(x2_vals, y2_vals, linestyle=':')\n",
    "        d2l.plt.legend(legend)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "和线性回归一样，多项式函数拟合也使用平方损失函数。因为我们将尝试使用不同复杂度的模型来拟合生成的数据集，所以我们把模型定义部分放在fit_and_plot函数中。多项式函数拟合的训练和测试步骤与3.6节（softmax回归的从零开始实现）介绍的softmax回归中的相关步骤类似。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_epochs=100\n",
    "\n",
    "def fit_and_plot(train_features, test_features, train_labels, test_labels):\n",
    "    net = tf.keras.Sequential([tf.keras.layers.Dense(1)])\n",
    "    batch_size = min(10, train_labels.shape[0])\n",
    "#     batch_size = tf.cast(batch_size, 'int64')\n",
    "    train_iter = tf.data.Dataset.from_tensor_slices((train_features, train_labels)).batch(10) \n",
    "    optimizer = tf.keras.optimizers.Adam()\n",
    "    train_ls, test_ls, loss_history = [], [], []\n",
    "    for _ in range(num_epochs):\n",
    "        for X, y in train_iter:\n",
    "            with tf.GradientTape() as tape:\n",
    "                logits = net(X, training=True)\n",
    "                l = tf.keras.losses.mse(logits, y)\n",
    "                print(l)\n",
    "\n",
    "            # 获取本批数据梯度\n",
    "            grads = tape.gradient(l, net.trainable_variables)\n",
    "            # 反向传播优化\n",
    "            optimizer.apply_gradients(zip(grads, net.trainable_variables))\n",
    "\n",
    "        train_ls.append(tf.keras.losses.mse(net(train_features), train_labels).numpy().mean())\n",
    "        test_ls.append(tf.keras.losses.mse(net(test_features),test_labels).numpy().mean())\n",
    "    print('final epoch: train loss', train_ls[-1], 'test loss', test_ls[-1])\n",
    "    semilogy(range(1, num_epochs + 1), train_ls, 'epochs', 'loss',\n",
    "             range(1, num_epochs + 1), test_ls, ['train', 'test'])\n",
    "    print('weight:', net.get_weights()[0],\n",
    "          '\\nbias:', net.get_weights()[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.4.3. 三阶多项式函数拟合（正常）¶\n",
    "我们先使用与数据生成函数同阶的三阶多项式函数拟合。实验表明，这个模型的训练误差和在测试数据集的误差都较低。训练出的模型参数也接近真实值： w1=1.2,w2=−3.4,w3=5.6,b=5 。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "pycharm": {
     "is_executing": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(\n",
      "[946.929   674.59    692.5846  985.0542  678.06775 684.7721  672.81116\n",
      " 676.75543 665.8366  645.04175], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.21875 284.6864  284.7417  284.75018 288.5014  288.09827 284.70673\n",
      " 322.98917 347.72964 338.0213 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 789.8026   753.1981   802.34955  753.1635   787.05835  779.7846\n",
      " 1562.3325   792.27625  840.7122   825.4679 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2997.4805 1860.1555 1830.4426 1864.4277 1857.0983 1848.0719 1883.6656\n",
      " 1961.4812 1838.275  1772.6338], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.49876   67.78921   77.20399   78.84548   71.786224  79.14293\n",
      "  81.61726  157.02948   70.98347   75.1135  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[50.38317  24.020054 34.42257  27.705982 32.904305 31.659832 22.624985\n",
      " 24.49998  54.04889  32.268364], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[378.95007 309.8639  442.24234 477.00912 407.28    393.53632 516.9403\n",
      " 444.5855  478.53107 809.7923 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2153.4878   942.84296 1024.5867  1011.7096   962.44495 1033.9106\n",
      " 1159.4929  1103.2781   951.7985  1023.62744], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.91638 246.05522 228.51567 230.7081  228.21245 225.84343 256.50906\n",
      " 228.35002 279.42468 235.18002], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[214.00505 209.92854 273.3458  209.52454 209.4779  240.2622  212.98001\n",
      " 211.25998 209.1918  212.33426], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[943.90985 674.6239  692.46655 981.55505 678.0736  684.7217  672.85876\n",
      " 676.7721  665.9332  645.20197], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.20126 284.68594 284.7418  284.7478  288.4544  288.0319  284.70703\n",
      " 322.47382 346.87283 337.1156 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 789.87024  753.3918   802.334    753.3571   787.14154  779.9059\n",
      " 1552.6501   792.3292   840.3168   825.23016], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2985.917  1860.1277 1830.6469 1864.3717 1857.092  1848.1345 1883.4781\n",
      " 1960.6946 1838.4183 1773.0701], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.48775   67.77951   77.20921   78.83955   71.816086  79.13474\n",
      "  81.58715  156.04762   71.01484   75.13045 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[50.162266 24.045599 34.38879  27.721207 32.88526  31.6512   22.645605\n",
      " 24.525333 53.782005 32.254852], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[378.9982  310.15738 441.71396 476.1128  407.10748 393.4909  515.60565\n",
      " 444.0328  477.61835 804.9523 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2139.819    943.1505  1024.4045  1011.64435  962.6615  1033.6368\n",
      " 1157.9276  1102.3046   952.0658  1023.4543 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.9111  245.79976 228.50468 230.6709  228.20451 225.83833 256.09805\n",
      " 228.34074 278.6823  235.08199], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.95003 209.91353 272.59128 209.51997 209.471   239.72708 212.91045\n",
      " 211.22102 209.19083 212.29822], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[941.67444 674.6978  692.4178  978.9469  678.1194  684.721   672.9471\n",
      " 676.8284  666.072   645.39343], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.19174 284.68524 284.74292 284.74442 288.42355 287.95618 284.708\n",
      " 322.07205 346.19205 336.16803], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 789.9127   753.5563   802.2992   753.5216   787.19836  779.9978\n",
      " 1543.028    792.3584   839.89355  824.96796], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2975.3113 1860.1252 1830.874  1864.343  1857.1088 1848.217  1883.3333\n",
      " 1960.0123 1838.5837 1773.5303], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.47199  67.77156  77.20955  78.82884  71.84101  79.12179  81.55192\n",
      " 155.04408  71.04152  75.14229], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[49.93545  24.068638 34.351936 27.733387 32.86336  31.639736 22.664719\n",
      " 24.548008 53.50874  32.238518], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.03888 310.44037 441.1795  475.21118 406.92944 393.4401  514.26764\n",
      " 443.47403 476.7003  800.1377 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2126.2676   943.4451  1024.2166  1011.57324  962.8668  1033.3573\n",
      " 1156.3602  1101.3262   952.321   1023.27576], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.9051  245.54333 228.49304 230.63277 228.19588 225.83359 255.6865\n",
      " 228.33073 277.96588 234.98283], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.89795 209.89824 271.8628  209.51591 209.46391 239.1927  212.84036\n",
      " 211.18161 209.1901  212.26431], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[939.50555 674.7747  692.37463 976.4149  678.16815 684.7242  673.0383\n",
      " 676.8876  666.21405 645.58923], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.18304 284.68457 284.74414 284.74097 288.39453 287.88046 284.70905\n",
      " 321.684   345.53287 335.22546], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 789.95154  753.71704  802.2616   753.6825   787.2511   780.08527\n",
      " 1533.4702   792.3839   839.4673   824.703  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2964.9146 1860.1267 1831.1051 1864.3191 1857.1289 1848.3035 1883.1957\n",
      " 1959.3494 1838.752  1773.9968], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.4554   67.76448  77.20897  78.81732  71.86504  79.10802  81.51591\n",
      " 154.04373  71.06736  75.15317], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[49.708668 24.091188 34.314552 27.744892 32.840908 31.627705 22.683659\n",
      " 24.57013  53.235718 32.221626], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.07745 310.72162 440.64508 474.31113 406.7503  393.38788 512.9337\n",
      " 442.91534 475.784   795.35315], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2112.8164   943.73596 1024.0276  1011.5008   963.0685  1033.0767\n",
      " 1154.7974  1100.3494   952.57214 1023.09607], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.89893 245.28838 228.48123 230.59464 228.18701 225.82915 255.27768\n",
      " 228.3206  277.26132 234.88399], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.84697 209.88297 271.1457  209.51205 209.45679 238.663   212.7708\n",
      " 211.14246 209.1894  212.2312 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[937.3646  674.85236 692.3329  973.9155  678.2177  684.7284  673.13007\n",
      " 676.94763 666.35706 645.78766], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.17462 284.68393 284.74545 284.7376  288.36615 287.80557 284.71014\n",
      " 321.30185 344.88336 334.2923 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 789.9892   753.87726  802.2234   753.84247  787.30273  780.1713\n",
      " 1523.9884   792.4085   839.042    824.438  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2954.6262 1860.1293 1831.3367 1864.2966 1857.1504 1848.39   1883.0608\n",
      " 1958.6937 1838.9213 1774.4684], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.4386    67.75815   77.208115  78.80555   71.88879   79.09401\n",
      "  81.479744 153.05028   71.092964  75.16372 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[49.482964 24.11361  34.27712  27.756155 32.81834  31.615509 22.702673\n",
      " 24.592089 52.96411  32.204582], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.1153  311.00296 440.1122  473.4148  406.57135 393.3353  511.6061\n",
      " 442.35834 474.8715  790.60144], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2099.4673   944.0251  1023.8387  1011.42804  963.26886 1032.7965\n",
      " 1153.2413  1099.3761   952.82196 1022.9165 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.89273 245.03545 228.46939 230.55661 228.17815 225.82483 254.8724\n",
      " 228.31042 276.56503 234.7858 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.79668 209.86789 270.43643 209.50826 209.44974 238.13907 212.70198\n",
      " 211.10371 209.18872 212.19853], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[935.2418  674.93    692.2917  971.4372  678.26746 684.7329  673.22217\n",
      " 677.0077  666.49994 645.9884 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.16635 284.68332 284.74677 284.73438 288.33807 287.73163 284.71124\n",
      " 320.92374 344.24063 333.36993], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.0262   754.0376   802.1848   754.00275  787.3537   780.25684\n",
      " 1514.5864   792.43256  838.61816  824.1737 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2944.4204 1860.1326 1831.568  1864.2748 1857.1719 1848.4766 1882.9268\n",
      " 1958.0427 1839.0902 1774.9436], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.42176   67.75253   77.20714   78.7937    71.91241   79.07994\n",
      "  81.443634 152.0648    71.11846   75.174126], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[49.258675 24.13601  34.239773 27.767307 32.795784 31.603271 22.721828\n",
      " 24.614002 52.694298 32.187534], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.15274 311.28485 439.5816  472.52277 406.39276 393.28265 510.28574\n",
      " 441.8037  473.96344 785.8841 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2086.2224   944.3135  1023.6501  1011.355    963.46814 1032.5171\n",
      " 1151.6931  1098.4069   953.0709  1022.737  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.8865  244.78482 228.4576  230.51884 228.16931 225.82071 254.47095\n",
      " 228.30026 275.876   234.68832], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.74687 209.85295 269.73383 209.50449 209.44278 237.62112 212.63399\n",
      " 211.06538 209.18808 212.16621], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[933.134   675.0077  692.25104 968.97687 678.3172  684.7377  673.3142\n",
      " 677.06793 666.6431  646.19104], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.15817 284.6828  284.74805 284.73123 288.3103  287.65875 284.7124\n",
      " 320.54904 343.6037  332.4585 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.0631   754.1981   802.14636  754.1632   787.4044   780.3418\n",
      " 1505.2656   792.4564   838.1964   823.9105 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2934.2893 1860.1361 1831.7992 1864.2533 1857.1941 1848.5637 1882.794\n",
      " 1957.3951 1839.259  1775.4221], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.40493   67.74761   77.206116  78.78185   71.93599   79.06589\n",
      "  81.40762  151.08763   71.14394   75.18445 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[49.03589  24.158424 34.202557 27.778387 32.77328  31.591034 22.741152\n",
      " 24.635902 52.42637  32.170506], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.1899  311.56763 439.05322 471.63525 406.21478 393.23013 508.97275\n",
      " 441.25156 473.05988 781.2014 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2073.0818   944.6011  1023.4622  1011.2824   963.667   1032.2386\n",
      " 1150.1526  1097.4421   953.31915 1022.5583 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.88028 244.53653 228.4458  230.4813  228.16049 225.8167  254.07333\n",
      " 228.29016 275.19373 234.59167], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.69751 209.83818 269.0375  209.50076 209.43587 237.10928 212.56674\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 211.02756 209.18745 212.13419], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[931.0399  675.08527 692.2107  966.53284 678.36694 684.7425  673.40594\n",
      " 677.1279  666.78613 646.3958 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.15005 284.68234 284.7494  284.72818 288.28278 287.58698 284.71353\n",
      " 320.17743 342.97217 331.5582 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.0997   754.35913  802.10803  754.3243   787.4549   780.4267\n",
      " 1496.0261   792.4799   837.77655  823.64856], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2924.229  1860.1394 1832.0306 1864.2318 1857.2158 1848.6498 1882.6615\n",
      " 1956.7506 1839.4275 1775.9039], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.388115  67.74337   77.20506   78.77002   71.95952   79.05184\n",
      "  81.37175  150.11879   71.16942   75.19472 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[48.814636 24.180872 34.165485 27.789425 32.750843 31.578817 22.760647\n",
      " 24.657806 52.16035  32.153515], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.2269  311.85123 438.52734 470.75238 406.0374  393.17764 507.6673\n",
      " 440.70197 472.16113 776.5535 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2060.0457   944.88837 1023.2746  1011.20966  963.8654  1031.9609\n",
      " 1148.6202  1096.482    953.5668  1022.38   ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.87411 244.29053 228.43411 230.444   228.1517  225.81279 253.67966\n",
      " 228.28006 274.51813 234.4958 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.64859 209.82361 268.34717 209.49707 209.42908 236.60344 212.5004\n",
      " 210.99023 209.18681 212.10242], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[928.9595  675.1626  692.1704  964.105   678.4165  684.74725 673.4977\n",
      " 677.18787 666.9293  646.6024 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.14197 284.68195 284.75073 284.72525 288.2554  287.5163  284.7147\n",
      " 319.80893 342.34586 330.66898], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.1362   754.5206   802.0697   754.48584  787.50525  780.51117\n",
      " 1486.8674   792.5035   837.359    823.3877 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2914.2388 1860.143  1832.2611 1864.2107 1857.2377 1848.7363 1882.5295\n",
      " 1956.1091 1839.5963 1776.3894], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.37135   67.7398    77.20399   78.758194  71.98305   79.03783\n",
      "  81.33601  149.15834   71.19491   75.20495 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[48.59492  24.203354 34.128563 27.800415 32.728474 31.566626 22.780321\n",
      " 24.679722 51.896263 32.136574], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.26367 312.1357  438.0038  469.87408 405.86063 393.12524 506.36945\n",
      " 440.1548  471.2671  771.9403 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2047.1139   945.1753  1023.08777 1011.1371   964.0631  1031.6844\n",
      " 1147.0961  1095.5261   953.81415 1022.20233], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.86795 244.04683 228.42244 230.40695 228.14294 225.80908 253.2898\n",
      " 228.26999 273.84903 234.40073], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.60013 209.80925 267.66278 209.49345 209.42233 236.10368 212.43486\n",
      " 210.95332 209.18619 212.07092], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[926.8923  675.24    692.13043 961.69275 678.466   684.75214 673.58923\n",
      " 677.2477  667.0722  646.81104], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.13397 284.68158 284.7521  284.72235 288.22824 287.4467  284.71588\n",
      " 319.44336 341.72467 329.7907 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.1725   754.6825   802.0314   754.64764  787.55536  780.5956\n",
      " 1477.7898   792.52686  836.94366  823.12805], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2904.3174 1860.1465 1832.4916 1864.1901 1857.26   1848.8226 1882.3984\n",
      " 1955.4707 1839.7644 1776.8782], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.35465   67.7369    77.202896  78.74641   72.00654   79.02385\n",
      "  81.30042  148.20618   71.22038   75.21513 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[48.376736 24.225872 34.091797 27.811367 32.706177 31.554453 22.800167\n",
      " 24.70165  51.634083 32.119675], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.3003  312.42105 437.48273 469.0004  405.6845  393.073   505.07895\n",
      " 439.6103  470.37775 767.3617 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2034.2864   945.4613  1022.9017  1011.0648   964.26056 1031.4089\n",
      " 1145.5798  1094.5751   954.0607  1022.02527], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.86182 243.80551 228.41084 230.37016 228.13423 225.80545 252.90381\n",
      " 228.26001 273.18646 234.30644], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.552   209.79504 266.98425 209.48979 209.41573 235.6099  212.37016\n",
      " 210.91692 209.18555 212.03972], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[924.8379  675.31714 692.0905  959.2964  678.5155  684.7572  673.6808\n",
      " 677.30743 667.2151  647.0216 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.126   284.68124 284.75342 284.71967 288.20126 287.3781  284.7171\n",
      " 319.08075 341.10864 328.9234 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.20874  754.8449   801.9933   754.8101   787.6053   780.6799\n",
      " 1468.7926   792.5502   836.5301   822.8695 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2894.4646 1860.1501 1832.7214 1864.1692 1857.282  1848.9086 1882.2676\n",
      " 1954.8346 1839.932  1777.3698], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.33797   67.73467   77.20178   78.73462   72.03002   79.009895\n",
      "  81.26495  147.26228   71.24587   75.225266], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[48.160072 24.248423 34.055183 27.822275 32.68396  31.542313 22.820187\n",
      " 24.72359  51.3738   32.102825], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.33676 312.70734 436.96396 468.1313  405.50897 393.02087 503.796\n",
      " 439.0682  469.49307 762.8174 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2021.5621  945.7471 1022.716  1010.9927  964.4572 1031.134  1144.0719\n",
      " 1093.6282  954.3068 1021.8485], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.85567 243.5664  228.39926 230.33362 228.12553 225.802   252.52158\n",
      " 228.25003 272.53027 234.21297], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.50432 209.781   266.31165 209.48624 209.40915 235.12202 212.30627\n",
      " 210.88095 209.18494 212.00876], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[922.79675 675.39417 692.0509  956.91534 678.56476 684.7621  673.77203\n",
      " 677.367   667.3579  647.234  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.1181  284.681   284.75482 284.71698 288.1745  287.3106  284.71832\n",
      " 318.72113 340.49765 328.06686], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.24475  755.0078   801.95514  754.973    787.65515  780.7638\n",
      " 1459.8752   792.5733   836.1188   822.6121 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2884.681  1860.1537 1832.9509 1864.1487 1857.3037 1848.9944 1882.1373\n",
      " 1954.2019 1840.0992 1777.8652], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.32135   67.7331    77.20066   78.72288   72.05349   78.995964\n",
      "  81.22963  146.32661   71.27138   75.23535 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[47.94491  24.271015 34.018715 27.83315  32.66181  31.530193 22.840382\n",
      " 24.745544 51.11541  32.086025], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.37305 312.9944  436.44766 467.26675 405.33408 392.96884 502.52042\n",
      " 438.52872 468.6131  758.30743], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2008.9408   946.0322  1022.53094 1010.92053  964.6536  1030.8606\n",
      " 1142.5715  1092.6859   954.55255 1021.67255], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.84956 243.32959 228.38777 230.29732 228.1169  225.79868 252.14322\n",
      " 228.24011 271.88046 234.12027], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.45706 209.76717 265.64478 209.48264 209.40268 234.64009 212.2432\n",
      " 210.84543 209.18433 211.97807], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[920.76843 675.47107 692.0114  954.5496  678.614   684.76697 673.86316\n",
      " 677.4264  667.50073 647.44824], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.11026 284.6808  284.75616 284.71445 288.14792 287.24414 284.71954\n",
      " 318.3644  339.8917  327.22113], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.2806   755.1712   801.9171   755.13635  787.7047   780.8476\n",
      " 1451.0374   792.59644  835.70935  822.35583], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2874.9653 1860.1575 1833.1804 1864.1277 1857.3254 1849.0798 1882.0076\n",
      " 1953.5717 1840.2666 1778.3633], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.304756  67.73218   77.19951   78.71116   72.07693   78.982086\n",
      "  81.19444  145.39914   71.29689   75.245415], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[47.731255 24.29364  33.9824   27.843988 32.63974  31.518108 22.860744\n",
      " 24.767508 50.8589   32.069267], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.40915 313.28232 435.9337  466.40674 405.1598  392.91693 501.2523\n",
      " 437.99176 467.7377  753.83154], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1996.4222   946.317   1022.34656 1010.84863  964.8494  1030.5879\n",
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      "tf.Tensor(\n",
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      " 228.23022 271.237   234.02835], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.41019 209.75351 264.9837  209.47913 209.39629 234.16402 212.18088\n",
      " 210.81038 209.18375 211.94763], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[918.7531  675.54785 691.9721  952.1992  678.6631  684.77203 673.9542\n",
      " 677.4859  667.64343 647.66437], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.10245 284.68066 284.75754 284.712   288.12152 287.1787  284.7208\n",
      " 318.0105  339.2907  326.38614], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.3163   755.3349   801.87915  755.3002   787.7542   780.93115\n",
      " 1442.2786   792.61945  835.30225  822.10077], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2865.3176 1860.1614 1833.4092 1864.1072 1857.3477 1849.1656 1881.8783\n",
      " 1952.9443 1840.4332 1778.8652], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.288216  67.731895  77.198364  78.69944   72.10036   78.96822\n",
      "  81.159386 144.47975   71.32239   75.25543 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[47.519093 24.316303 33.946228 27.854786 32.617737 31.506046 22.881275\n",
      " 24.789488 50.604244 32.052563], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.4452  313.57114 435.42206 465.55127 404.98615 392.8651  499.99152\n",
      " 437.4572  466.867   749.3895 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1984.0055   946.60126 1022.1627  1010.777    965.0449  1030.3162\n",
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      "tf.Tensor(\n",
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      " 228.22041 270.59982 233.93718], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.3637  209.74002 264.3283  209.47566 209.38998 233.69376 212.11942\n",
      " 210.77579 209.18315 211.91748], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[916.7503  675.62445 691.933   949.8641  678.7122  684.777   674.04504\n"
     ]
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     "output_type": "stream",
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      " 677.54517 667.7861  647.8823 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
      "[ 790.3519   755.49915  801.84143  755.4645   787.8035   781.0145\n",
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      "[2855.7368 1860.1653 1833.638  1864.0869 1857.3695 1849.251  1881.7496\n",
      " 1952.3197 1840.5996 1779.3695], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.27172   67.732254  77.19719   78.68776   72.123764  78.9544\n",
      "  81.124466 143.56845   71.34791   75.26541 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[47.30842  24.338999 33.91021  27.86555  32.595814 31.494013 22.901978\n",
      " 24.811478 50.351456 32.035904], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.48102 313.86075 434.9129  464.70035 404.81305 392.81342 498.73804\n",
      " 436.9252  466.0009  744.98114], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 1138.119   1089.8856   955.28674 1021.14795], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.83134 242.63266 228.35355 230.18991 228.09111 225.78947 251.03052\n",
      " 228.21062 269.96887 233.84676], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.31763 209.72672 263.67856 209.47214 209.38376 233.22925 212.05869\n",
      " 210.74167 209.18253 211.88754], shape=(10,), dtype=float32)\n",
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      "[914.7604  675.70105 691.89404 947.54395 678.76117 684.7821  674.13586\n",
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      "tf.Tensor(\n",
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      "tf.Tensor(\n",
      "[ 790.38745  755.66394  801.8036   755.6292   787.85254  781.09784\n",
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      "[2846.2236 1860.169  1833.8665 1864.0667 1857.3914 1849.3363 1881.6215\n",
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      "tf.Tensor(\n",
      "[ 79.25526   67.73326   77.19601   78.676094  72.14715   78.94061\n",
      "  81.08968  142.66518   71.37343   75.275345], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[47.099213 24.36173  33.87434  27.876276 32.573956 31.482006 22.92284\n",
      " 24.833477 50.100506 32.019295], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.51666 314.15112 434.40594 463.85382 404.64056 392.76187 497.49185\n",
      " 436.3957  465.13934 740.6062 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1959.4752   947.1686  1021.79675 1010.6341   965.43427 1029.7756\n",
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      "tf.Tensor(\n",
      "[227.82532 242.40483 228.34224 230.15459 228.0826  225.7867  250.66704\n",
      " 228.20085 269.34418 233.75716], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.2719  209.71355 263.03458 209.46875 209.37764 232.77048 211.99878\n",
      " 210.70793 209.18196 211.85788], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[912.783   675.77747 691.8552  945.2389  678.81006 684.7872  674.22644\n",
      " 677.6634  668.07117 648.3236 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.0793  284.6805  284.76178 284.70526 288.0435  286.98862 284.72467\n",
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      "tf.Tensor(\n",
      "[ 790.4227   755.8291   801.7659   755.7943   787.90155  781.18085\n",
      " 1416.4713   792.6876   834.0928   821.34216], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2836.7764 1860.1732 1834.0944 1864.0466 1857.4135 1849.4213 1881.4935\n",
      " 1951.0791 1840.9314 1780.3881], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.238846  67.734886  77.1948    78.66446   72.17053   78.92685\n",
      "  81.05503  141.76984   71.39895   75.28525 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[46.89147  24.384495 33.838615 27.886967 32.552177 31.470028 22.943869\n",
      " 24.855492 49.851387 32.002735], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.5522  314.44238 433.90137 463.01178 404.46872 392.7104  496.25287\n",
      " 435.86865 464.28232 736.2645 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1947.361    947.4513  1021.61487 1010.5631   965.62823 1029.5068\n",
      " 1135.19    1088.041    955.77374 1020.8009 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.8193  242.17912 228.33101 230.1195  228.07413 225.78398 250.3072\n",
      " 228.19116 268.72562 233.66826], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.22661 209.70059 262.39612 209.4653  209.37155 232.31746 211.93967\n",
      " 210.67468 209.18135 211.82846], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[910.8182  675.85364 691.8167  942.9487  678.85876 684.79224 674.31696\n",
      " 677.7223  668.2137  648.547  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.07172 284.68057 284.76318 284.7032  288.01782 286.92728 284.72598\n",
      " 316.6236  336.93622 323.15137], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.4581   755.9946   801.72845  755.95984  787.9505   781.2637\n",
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      "tf.Tensor(\n",
      "[2827.3962 1860.1774 1834.322  1864.0267 1857.4353 1849.5061 1881.3665\n",
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      "tf.Tensor(\n",
      "[ 79.22247  67.73714  77.19359  78.65285  72.19389  78.91312  81.02052\n",
      " 140.88245  71.42447  75.2951 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[46.685196 24.407291 33.803043 27.897617 32.530468 31.458075 22.965057\n",
      " 24.877514 49.604095 31.986216], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.58755 314.73438 433.3991  462.17422 404.29752 392.6591  495.02124\n",
      " 435.34406 463.42993 731.95605], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1935.3461   947.734   1021.4333  1010.4917   965.8219  1029.2389\n",
      " 1133.7373  1087.125    956.0165  1020.62823], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.81332 241.95569 228.31978 230.08467 228.06567 225.78145 249.95102\n",
      " 228.18147 268.11322 233.58012], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.18169 209.68782 261.76328 209.46194 209.36557 231.87004 211.88132\n",
      " 210.64185 209.18076 211.79932], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[908.8656  675.9298  691.7783  940.6735  678.90753 684.79736 674.4073\n",
      " 677.7811  668.3561  648.77203], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.06415 284.68066 284.76465 284.70123 287.99237 286.8669  284.7273\n",
      " 316.28387 336.35977 322.36868], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.49304  756.1605   801.691    756.12585  787.99915  781.3463\n",
      " 1399.653    792.7326   833.2966   820.8419 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2818.082  1860.1813 1834.5494 1864.0068 1857.4574 1849.5906 1881.24\n",
      " 1949.8496 1841.2621 1781.4183], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.20616   67.740005  77.19237   78.64125   72.21722   78.89942\n",
      "  80.986145 140.00293   71.450005  75.30492 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[46.48037  24.43012  33.767616 27.908237 32.50883  31.446148 22.986404\n",
      " 24.899548 49.35862  31.969748], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.62274 315.02716 432.89923 461.34106 404.12686 392.60785 493.7967\n",
      " 434.82184 462.58203 727.68054], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1923.4309   948.01575 1021.2523  1010.4211   966.01495 1028.9719\n",
      " 1132.2922  1086.2136   956.25867 1020.45605], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.80733 241.73438 228.30867 230.05008 228.05725 225.779   249.59848\n",
      " 228.17184 267.5069  233.49275], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.13716 209.67517 261.13596 209.45859 209.35965 231.42825 211.82373\n",
      " 210.60947 209.1802  211.77036], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[906.92566 676.0058  691.74    938.4131  678.95605 684.80237 674.49744\n",
      " 677.83997 668.4982  648.9989 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.05667 284.68082 284.76608 284.69937 287.96707 286.80756 284.7287\n",
      " 315.94696 335.78815 321.59622], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.528    756.32697  801.65344  756.29236  788.04767  781.42883\n",
      " 1391.3582   792.7549   832.90137  820.59357], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2808.8335 1860.1853 1834.7764 1863.987  1857.4792 1849.675  1881.1136\n",
      " 1949.2385 1841.4275 1781.9381], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.18988   67.74348   77.191124  78.629684  72.24053   78.885765\n",
      "  80.95189  139.13124   71.47554   75.314705], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[46.276985 24.452982 33.73233  27.918814 32.487267 31.43425  23.00791\n",
      " 24.921589 49.11494  31.953327], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.65778 315.32065 432.4016  460.51227 403.95682 392.55673 492.57935\n",
      " 434.3021  461.7386  723.4378 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1911.6136  948.2972 1021.0721 1010.3502  966.2075 1028.7058 1130.8551\n",
      " 1085.3064  956.5005 1020.2845], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.80142 241.51523 228.29756 230.01567 228.04887 225.7767  249.24948\n",
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      "tf.Tensor(\n",
      "[213.09299 209.66269 260.5141  209.45528 209.35385 230.99207 211.76692\n",
      " 210.57751 209.17964 211.74173], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[904.9979  676.08167 691.7019  936.16736 679.0047  684.8076  674.5875\n",
      " 677.89856 668.64044 649.2274 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.04922 284.68106 284.76752 284.69757 287.94196 286.7492  284.73004\n",
      " 315.61282 335.22122 320.83392], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.56287  756.4937   801.6162   756.4591   788.096    781.511\n",
      " 1383.1392   792.7772   832.5084   820.3463 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2799.6492 1860.1895 1835.0029 1863.9674 1857.5013 1849.7594 1880.9883\n",
      " 1948.6309 1841.592  1782.4603], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.17363   67.74757   77.189865  78.61814   72.26384   78.87214\n",
      "  80.91778  138.2673    71.501076  75.32443 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[46.075035 24.47587  33.69719  27.929358 32.46577  31.422379 23.029568\n",
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      "tf.Tensor(\n",
      "[379.69263 315.61493 431.90634 459.6879  403.7874  392.50577 491.36905\n",
      " 433.78482 460.89972 719.22766], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1899.8943   948.5781  1020.8926  1010.2798   966.3997  1028.4409\n",
      " 1129.4255  1084.4036   956.7418  1020.11346], shape=(10,), dtype=float32)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(\n",
      "[227.79546 241.29819 228.2865  229.98154 228.0405  225.77457 248.90413\n",
      " 228.15274 266.31235 233.32016], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.04922 209.65042 259.89777 209.45198 209.34807 230.5614  211.71086\n",
      " 210.54597 209.17908 211.71329], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[903.0827  676.1574  691.66394 933.9364  679.0531  684.81287 674.6774\n",
      " 677.95715 668.7826  649.4576 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.0418  284.6813  284.769   284.6959  287.91705 286.6918  284.73138\n",
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      "tf.Tensor(\n",
      "[ 790.59753  756.6609   801.5789   756.6264   788.1442   781.59314\n",
      " 1374.9955   792.79926  832.1172   820.1001 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2790.5312 1860.1936 1835.2292 1863.948  1857.5228 1849.8431 1880.863\n",
      " 1948.0251 1841.7562 1782.9857], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.15745   67.75226   77.18858   78.60662   72.28712   78.858536\n",
      "  80.8838   137.41112   71.52661   75.334145], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[45.87451  24.498787 33.662193 27.939869 32.444355 31.410534 23.051382\n",
      " 24.965694 48.632946 31.920628], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.7274  315.90994 431.41333 458.86786 403.61856 392.4549  490.16586\n",
      " 433.26993 460.06512 715.0498 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1888.2727   948.85876 1020.7134  1010.2095   966.5913  1028.1766\n",
      " 1128.0037  1083.5049   956.98254 1019.943  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.78952 241.08334 228.27548 229.94766 228.0322  225.7725  248.5623\n",
      " 228.14322 265.72406 233.23502], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[213.00581 209.63828 259.28693 209.44868 209.3424  230.13623 211.65556\n",
      " 210.51492 209.17851 211.6851 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[901.1795  676.23303 691.6263  931.71985 679.10144 684.8181  674.7672\n",
      " 678.0155  668.9247  649.6895 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.0345  284.6816  284.77048 284.69427 287.8923  286.6354  284.73282\n",
      " 314.95273 334.10175 319.33966], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.63214  756.8285   801.5417   756.794    788.19214  781.675\n",
      " 1366.9268   792.8212   831.728    819.855  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2781.4773 1860.1982 1835.4551 1863.929  1857.5453 1849.9275 1880.7379\n",
      " 1947.4229 1841.9202 1783.5139], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.141304  67.75753   77.18731   78.59514   72.31036   78.84496\n",
      "  80.84993  136.56259   71.552155  75.3438  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[45.675404 24.521732 33.62735  27.950338 32.423004 31.398718 23.073347\n",
      " 24.987757 48.39461  31.904346], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.76202 316.2057  430.92255 458.0522  403.4503  392.4041  488.96973\n",
      " 432.75748 459.23517 710.9042 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1876.748    949.1387  1020.53467 1010.13916  966.7826  1027.9136\n",
      " 1126.5892  1082.6106   957.2228  1019.7731 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.78365 240.8706  228.26457 229.91397 228.0239  225.77055 248.22397\n",
      " 228.13374 265.14175 233.15056], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.9628  209.62631 258.68146 209.44547 209.33679 229.71655 211.601\n",
      " 210.4842  209.17795 211.65718], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[899.2886  676.3085  691.5886  929.5179  679.1496  684.82324 674.8568\n",
      " 678.07385 669.0665  649.92303], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.02716 284.68198 284.77197 284.6928  287.86774 286.57993 284.73422\n",
      " 314.62677 333.549   318.60754], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.6665   756.99646  801.50476  756.962    788.24005  781.7567\n",
      " 1358.9325   792.84314  831.34094  819.61096], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2772.4883 1860.2024 1835.6809 1863.9092 1857.5667 1850.0111 1880.6136\n",
      " 1946.8225 1842.0836 1784.0452], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.125206  67.76341   77.186005  78.58365   72.333595  78.83143\n",
      "  80.81622  135.72174   71.57768   75.353424], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[45.477715 24.544704 33.592644 27.960773 32.401726 31.386929 23.095459\n",
      " 25.009829 48.158043 31.888113], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.79645 316.5021  430.43414 457.2408  403.28262 392.35352 487.78067\n",
      " 432.2474  458.40952 706.7908 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1865.3201   949.41815 1020.35675 1010.06915  966.97327 1027.6514\n",
      " 1125.1829  1081.7206   957.4626  1019.6035 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.77776 240.65991 228.25366 229.88057 228.01566 225.76875 247.88916\n",
      " 228.12431 264.5653  233.06685], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.92014 209.61455 258.08133 209.44226 209.33127 229.30234 211.54716\n",
      " 210.45393 209.17741 211.62947], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[897.4098  676.3838  691.5513  927.33026 679.1978  684.82855 674.94635\n",
      " 678.132   669.2085  650.1582 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.0199  284.68237 284.7735  284.69138 287.84332 286.52545 284.73566\n",
      " 314.30353 333.00104 317.8853 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.70087  757.16486  801.46765  757.1304   788.2878   781.8382\n",
      " 1351.012    792.8649   830.95575  819.368  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2763.5627 1860.2067 1835.9059 1863.8903 1857.5885 1850.095  1880.4899\n",
      " 1946.2253 1842.2471 1784.5785], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.10913   67.76986   77.18471   78.57221   72.356804  78.817924\n",
      "  80.78262  134.88846   71.603226  75.363014], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[45.28142  24.567701 33.55808  27.97117  32.380516 31.375164 23.117718\n",
      " 25.031902 47.923225 31.871927], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.83072 316.79922 429.9479  456.43378 403.11557 392.30292 486.59857\n",
      " 431.73975 457.58838 702.70905], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1853.987    949.69714 1020.1794  1009.9993   967.1636  1027.3901\n",
      " 1123.7834  1080.8348   957.7018  1019.43494], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.77188 240.45137 228.24283 229.84732 228.00745 225.76704 247.55783\n",
      " 228.1149  263.99475 232.98386], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.87785 209.6029  257.48657 209.43904 209.32584 228.89343 211.49406\n",
      " 210.4241  209.17688 211.602  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[895.5428  676.4591  691.514   925.1569  679.2459  684.8338  675.03577\n",
      " 678.19006 669.3504  650.39496], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.0127  284.68283 284.77496 284.69006 287.81912 286.4719  284.73712\n",
      " 313.98294 332.45764 317.1729 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.735    757.3336   801.43085  757.29913  788.3353   781.9194\n",
      " 1343.1649   792.8866   830.57227  819.1261 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2754.7007 1860.2112 1836.1311 1863.8715 1857.6106 1850.1781 1880.3668\n",
      " 1945.6309 1842.4102 1785.1152], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.0931   67.7769   77.18339  78.56078  72.38     78.80445  80.74917\n",
      " 134.06273  71.62875  75.37256], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[45.08653  24.590725 33.52366  27.981531 32.359383 31.363428 23.140125\n",
      " 25.05398  47.69015  31.855785], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.86484 317.09702 429.46396 455.63104 402.94913 392.25253 485.42334\n",
      " 431.23447 456.77148 698.659  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1842.7498   949.9757  1020.0026  1009.9295   967.35333 1027.1298\n",
      " 1122.3921  1079.9534   957.9404  1019.2667 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.76604 240.24487 228.23201 229.81436 227.99924 225.76546 247.22998\n",
      " 228.10559 263.43    232.90157], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.8359  209.5914  256.89713 209.43591 209.32048 228.48994 211.44174\n",
      " 210.39468 209.1763  211.57478], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[893.68787 676.5341  691.4769  922.9979  679.2939  684.8392  675.1249\n",
      " 678.24805 669.49207 650.6334 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[286.00552 284.68335 284.77646 284.6888  287.79507 286.4193  284.7386\n",
      " 313.665   331.91888 316.4702 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.7689   757.50275  801.394    757.46814  788.38275  782.0006\n",
      " 1335.3914   792.9084   830.19104  818.8854 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2745.902  1860.2156 1836.3552 1863.8528 1857.6326 1850.2611 1880.2439\n",
      " 1945.0388 1842.5725 1785.6539], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.07713   67.78451   77.18204   78.54937   72.40316   78.79101\n",
      "  80.715836 133.24448   71.65428   75.382065], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[44.893017 24.613773 33.489384 27.991858 32.33831  31.351719 23.162672\n",
      " 25.076061 47.45881  31.839695], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.89883 317.3955  428.98227 454.8326  402.78323 392.20224 484.25507\n",
      " 430.73154 455.95908 694.6405 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1831.607    950.2536  1019.82635 1009.86     967.5426  1026.8702\n",
      " 1121.008   1079.0759   958.1789  1019.09894], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.76025 240.04044 228.22128 229.78159 227.99112 225.76399 246.90552\n",
      " 228.09627 262.87106 232.81998], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.79439 209.58011 256.31296 209.43279 209.31519 228.09175 211.3901\n",
      " 210.36572 209.17581 211.5478 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[891.8451  676.6091  691.44    920.8534  679.3418  684.84436 675.214\n",
      " 678.30597 669.6336  650.8733 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.9984  284.6839  284.778   284.68768 287.77118 286.3676  284.74005\n",
      " 313.3498  331.3847  315.77728], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.80286  757.672    801.35724  757.6376   788.43005  782.0814\n",
      " 1327.6901   792.9298   829.8115   818.6456 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2737.1665 1860.2203 1836.5795 1863.8337 1857.6539 1850.3441 1880.1215\n",
      " 1944.4496 1842.7351 1786.1957], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.06119   67.792694  77.180695  78.537994  72.42629   78.7776\n",
      "  80.68263  132.43369   71.67981   75.39153 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[44.700897 24.63684  33.455246 28.002142 32.317314 31.340033 23.18536\n",
      " 25.098148 47.229195 31.823645], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.93268 317.69464 428.50284 454.0384  402.61798 392.15204 483.09375\n",
      " 430.23105 455.15097 690.6533 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1820.5582   950.5311  1019.65076 1009.79065  967.73145 1026.6117\n",
      " 1119.6316  1078.2029   958.4167  1018.93176], shape=(10,), dtype=float32)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(\n",
      "[227.75443 239.83804 228.21057 229.74905 227.98296 225.76265 246.5845\n",
      " 228.08699 262.3179  232.7391 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.7532  209.56894 255.73404 209.42964 209.30998 227.69882 211.33919\n",
      " 210.33708 209.1753  211.52107], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[890.01404 676.6839  691.4032  918.72253 679.3896  684.8499  675.30286\n",
      " 678.3638  669.7751  651.11487], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.99136 284.68448 284.7795  284.6866  287.7475  286.3169  284.74155\n",
      " 313.03714 330.85513 315.094  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.8367   757.8418   801.3207   757.8075   788.4771   782.1622\n",
      " 1320.061    792.95123  829.4341   818.407  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2728.4937 1860.2246 1836.8031 1863.8151 1857.6764 1850.4271 1879.9996\n",
      " 1943.8633 1842.8971 1786.7399], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.0453    67.80143   77.17932   78.52664   72.44941   78.76423\n",
      "  80.64956  131.63033   71.70534   75.400955], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[44.510143 24.659931 33.42125  28.012394 32.296394 31.328379 23.208187\n",
      " 25.120234 47.00128  31.807648], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.96628 317.99445 428.02557 453.24838 402.45328 392.10196 481.93927\n",
      " 429.73282 454.34717 686.6973 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1809.6029   950.8082  1019.47546 1009.7214   967.9198  1026.3541\n",
      " 1118.2625  1077.3339   958.65393 1018.76514], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.74866 239.63774 228.19992 229.71675 227.9749  225.76143 246.26689\n",
      " 228.07776 261.77045 232.65894], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.71233 209.55795 255.16037 209.42656 209.30481 227.31119 211.28902\n",
      " 210.30888 209.17476 211.49455], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[888.1948  676.75867 691.36664 916.60626 679.4373  684.8552  675.3917\n",
      " 678.42145 669.9165  651.35785], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.9843  284.68512 284.78107 284.68564 287.72397 286.2671  284.74304\n",
      " 312.72714 330.33008 314.42026], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.8702   758.012    801.28406  757.9776   788.524    782.24255\n",
      " 1312.5037   792.9725   829.0586   818.1695 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2719.8833 1860.2292 1837.0267 1863.7965 1857.698  1850.5101 1879.8785\n",
      " 1943.279  1843.059  1787.2869], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.02945   67.810745  77.17793   78.515305  72.47249   78.750885\n",
      "  80.616615 130.8343    71.73085   75.41034 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[44.32076  24.683046 33.387398 28.022604 32.275536 31.316748 23.23115\n",
      " 25.14232  46.77508  31.791687], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[379.99982 318.29483 427.5506  452.46265 402.28918 392.05197 480.79156\n",
      " 429.237   453.54776 682.7723 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1798.741    951.0846  1019.30115 1009.65234  968.10754 1026.0974\n",
      " 1116.9009  1076.4691   958.8905  1018.59894], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.74289 239.4394  228.18933 229.68466 227.96683 225.76028 245.95264\n",
      " 228.06856 261.22867 232.5795 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.67188 209.54712 254.59187 209.42355 209.29977 226.92871 211.23955\n",
      " 210.28108 209.17424 211.46826], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[886.3874  676.8331  691.3302  914.50354 679.4849  684.86066 675.48035\n",
      " 678.4789  670.05774 651.6024 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.97736 284.68585 284.7826  284.68475 287.7006  286.21817 284.74457\n",
      " 312.41974 329.8095  313.75595], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.9038   758.1823   801.24756  758.1481   788.5708   782.3229\n",
      " 1305.0175   792.9936   828.6849   817.933  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2711.3352 1860.2338 1837.2496 1863.7786 1857.7197 1850.5925 1879.7578\n",
      " 1942.6979 1843.2201 1787.8362], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 79.01365   67.82059   77.17656   78.50398   72.49557   78.737564\n",
      "  80.58379  130.0456    71.75636   75.41969 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[44.13273  24.706177 33.353683 28.03278  32.25475  31.305141 23.254253\n",
      " 25.164408 46.55057  31.775778], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.03314 318.59586 427.07782 451.68106 402.12564 392.00214 479.65063\n",
      " 428.7435  452.75253 678.8779 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1787.9713   951.3605  1019.12726 1009.5834   968.29504 1025.8419\n",
      " 1115.5464  1075.6086   959.1268  1018.4334 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.7371  239.24312 228.17874 229.65279 227.95879 225.75925 245.64175\n",
      " 228.05942 260.69254 232.50073], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.63174 209.53645 254.02852 209.4205  209.29472 226.55142 211.1908\n",
      " 210.2537  209.17374 211.44218], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[884.5915  676.9076  691.294   912.4149  679.5325  684.8661  675.5688\n",
      " 678.5364  670.19904 651.8485 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.97043 284.68655 284.78412 284.684   287.6774  286.17017 284.74615\n",
      " 312.11496 329.2934  313.10114], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 790.937    758.35315  801.2111   758.319    788.6173   782.403\n",
      " 1297.6022   793.01465  828.3131   817.6975 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2702.8484 1860.2389 1837.4723 1863.76   1857.742  1850.6748 1879.6377\n",
      " 1942.1191 1843.3811 1788.388 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.99788  67.83099  77.17513  78.49269  72.5186   78.72429  80.5511\n",
      " 129.26414  71.78187  75.429  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[43.94605  24.729328 33.320107 28.042913 32.23403  31.29356  23.277483\n",
      " 25.186493 46.327747 31.759912], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.06635 318.89746 426.60724 450.90366 401.96265 391.9524  478.5165\n",
      " 428.25235 451.96173 675.01434], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1777.2936   951.63605 1018.954   1009.5145   968.48206 1025.5869\n",
      " 1114.1995  1074.7522   959.3625  1018.2684 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.73137 239.04878 228.16824 229.62114 227.95078 225.75835 245.33414\n",
      " 228.05032 260.16202 232.4226 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.592   209.52596 253.4703  209.41751 209.28984 226.17923 211.14273\n",
      " 210.22672 209.17322 211.41635], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[882.80743 676.9818  691.25793 910.34015 679.57996 684.87146 675.6571\n",
      " 678.5937  670.3401  652.09607], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.96356 284.68732 284.7857  284.68326 287.65436 286.1231  284.74768\n",
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      "[ 790.97034  758.5242   801.1749   758.4901   788.6637   782.48285\n",
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      " 1941.5432 1843.5422 1788.9426], shape=(10,), dtype=float32)\n",
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      "[ 78.98214   67.841934  77.17371   78.48143   72.54161   78.71103\n",
      "  80.51854  128.48996   71.80736   75.43826 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[43.76071  24.752495 33.28667  28.053013 32.213387 31.282013 23.300846\n",
      " 25.208578 46.106606 31.744099], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.09943 319.19968 426.13885 450.13046 401.80032 391.90274 477.3891\n",
      " 427.7635  451.17505 671.18115], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1766.707    951.9108  1018.7811  1009.446    968.66833 1025.3333\n",
      " 1112.8599  1073.8997   959.59766 1018.1038 ], shape=(10,), dtype=float32)\n",
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      " 228.04121 259.63705 232.34518], shape=(10,), dtype=float32)\n",
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      "[212.55257 209.51555 252.91716 209.41455 209.28496 225.81213 211.09534\n",
      " 210.2001  209.17268 211.39078], shape=(10,), dtype=float32)\n",
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      "[881.0348  677.056   691.22205 908.2791  679.6273  684.87695 675.74536\n",
      " 678.651   670.4811  652.345  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.95673 284.68814 284.7873  284.68262 287.63153 286.07687 284.74927\n",
      " 311.5131  328.2746  311.81946], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.0034   758.6956   801.1386   758.66156  788.7101   782.5626\n",
      " 1282.9823   793.0566   827.5753   817.22974], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2686.0583 1860.2483 1837.9167 1863.7242 1857.7852 1850.8392 1879.3982\n",
      " 1940.9695 1843.7021 1789.4987], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.96648   67.85341   77.17227   78.47018   72.5646    78.6978\n",
      "  80.48611  127.72294   71.83284   75.447495], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[43.57671  24.77568  33.253376 28.063074 32.192802 31.270483 23.324337\n",
      " 25.230663 45.887115 31.728321], shape=(10,), dtype=float32)\n",
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      "tf.Tensor(\n",
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      " 1111.5276  1073.0514   959.83215 1017.93994], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.71997 238.6661  228.14737 229.55852 227.9349  225.75691 244.72888\n",
      " 228.03223 259.11765 232.26848], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.5135  209.50533 252.3691  209.41158 209.28018 225.45015 211.04868\n",
      " 210.17386 209.17221 211.3654 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[879.27374 677.13007 691.18634 906.23193 679.67456 684.8825  675.8334\n",
      " 678.7081  670.6219  652.59534], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.94992 284.68903 284.78888 284.68207 287.60886 286.03156 284.75082\n",
      " 311.21597 327.77182 311.19247], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.0364   758.8672   801.1024   758.83325  788.7561   782.6421\n",
      " 1275.7771   793.07733  827.20917  816.99756], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
      "[ 78.95082   67.865425  77.17082   78.458954  72.58755   78.684616\n",
      "  80.453804 126.96301   71.85832   75.45668 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[43.394035 24.798883 33.220215 28.073095 32.172295 31.258984 23.347956\n",
      " 25.252743 45.66929  31.712591], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.16504 319.80576 425.20868 448.59637 401.47736 391.8038  475.1543\n",
      " 426.79272 449.61444 663.60535], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1745.8063   952.45917 1018.4373  1009.3091   969.0397  1024.8282\n"
     ]
    },
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     "output_type": "stream",
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      " 1110.2024  1072.2073   960.0664  1017.77655], shape=(10,), dtype=float32)\n",
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      " 210.14807 209.17172 211.34024], shape=(10,), dtype=float32)\n",
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      "[877.52423 677.20386 691.15076 904.1981  679.7218  684.88806 675.92126\n",
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      "tf.Tensor(\n",
      "[ 791.0691   759.03925  801.06635  759.00525  788.8021   782.7213\n",
      " 1268.6409   793.0979   826.84503  816.76624], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2669.511  1860.2578 1838.3594 1863.6887 1857.8293 1851.0027 1879.1608\n",
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      "[ 78.93523   67.87795   77.16935   78.447754  72.610466  78.671455\n",
      "  80.421616 126.21022   71.88378   75.46583 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
      "[380.19763 320.10968 424.7469  447.83554 401.3167  391.75452 474.04688\n",
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      "tf.Tensor(\n",
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      " 228.01425 258.09537 232.11703], shape=(10,), dtype=float32)\n",
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      " 210.12263 209.17119 211.31534], shape=(10,), dtype=float32)\n",
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      "[875.78595 677.2775  691.11536 902.1781  679.7688  684.89355 676.00903\n",
      " 678.82196 670.90326 653.10046], shape=(10,), dtype=float32)\n",
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      "[285.9365  284.6909  284.79205 284.6812  287.56396 285.94354 284.75403\n",
      " 310.62933 326.77936 309.96597], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.10187  759.21155  801.03033  759.1776   788.8479   782.8004\n",
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      "[2661.3276 1860.263  1838.5803 1863.6711 1857.851  1851.0842 1879.043\n",
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      "tf.Tensor(\n",
      "[ 78.919655  67.89102   77.16788   78.43657   72.63337   78.65831\n",
      "  80.38956  125.464455  71.909225  75.47493 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 25.296894 45.238567 31.681269], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.23004 320.41412 424.28726 447.0788  401.15668 391.70535 472.9461\n",
      " 425.83115 448.0707  656.1493 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
      "[227.70303 238.10674 228.11641 229.46619 227.91129 225.75546 243.84537\n",
      " 228.00533 257.59238 232.04236], shape=(10,), dtype=float32)\n",
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      " 678.8788  671.0438  653.35504], shape=(10,), dtype=float32)\n",
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      "[ 791.1344   759.38403  800.9945   759.3502   788.8936   782.8794\n",
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      "tf.Tensor(\n",
      "[2653.2046 1860.2678 1838.8004 1863.6531 1857.8727 1851.1654 1878.9255\n",
      " 1938.7018 1844.3406 1791.7494], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.90414   67.90459   77.16638   78.42541   72.656235  78.64522\n",
      "  80.35762  124.72571   71.93468   75.48399 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[42.85392  24.86857  33.12156  28.102932 32.111168 31.224634 23.419552\n",
      " 25.318958 45.025658 31.665674], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.26227 320.71906 423.82977 446.32617 400.99722 391.65625 471.85187\n",
      " 425.35382 447.30508 652.46564], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1715.1267   953.2775  1017.9258  1009.10535  969.59314 1024.0774\n",
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      " 227.99641 257.0948  231.96834], shape=(10,), dtype=float32)\n",
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      "[212.36069 209.46597 250.22693 209.40005 209.26175 224.05197 210.86873\n",
      " 210.07292 209.17029 211.26614], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[872.3436  677.4246  691.045   898.1785  679.8627  684.90485 676.184\n",
      " 678.9354  671.18414 653.61096], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.92325 284.69293 284.79526 284.68073 287.5197  285.85907 284.75726\n",
      " 310.05267 325.80423 308.77557], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.1667   759.55676  800.95856  759.5231   788.939    782.95795\n",
      " 1247.6422   793.15924  825.7635   816.07886], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2645.14   1860.2731 1839.0203 1863.6361 1857.8945 1851.2467 1878.8088\n",
      " 1938.1412 1844.4998 1792.3171], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.88866   67.91868   77.16486   78.414276  72.67906   78.63215\n",
      "  80.325806 123.99391   71.9601    75.49301 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[42.67649  24.891825 33.088947 28.112799 32.09093  31.213236 23.443659\n",
      " 25.34102  44.814365 31.650122], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.2944  321.0245  423.37442 445.57755 400.83832 391.60727 470.7641\n",
      " 424.87875 446.54355 648.8115 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1705.0774   953.5493  1017.7565  1009.0377   969.7767  1023.8289\n",
      " 1104.9738  1068.8713   960.99744 1017.12805], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.69177 237.74345 228.096   229.40573 227.8957  225.7551  243.27234\n",
      " 227.9876  256.6026  231.89494], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.32332 209.45651 249.70374 209.39725 209.2573  223.71475 210.82544\n",
      " 210.04858 209.16977 211.24185], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[870.63934 677.498   691.0101  896.1987  679.90955 684.91034 676.2713\n",
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      "tf.Tensor(\n",
      "[285.9167  284.69403 284.79688 284.68057 287.49786 285.81805 284.75894\n",
      " 309.76807 325.32306 308.19376], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.19904  759.72986  800.92285  759.6962   788.9843   783.0365\n",
      " 1240.7778   793.1795   825.4066   815.85175], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2637.1345 1860.2777 1839.24   1863.6189 1857.916  1851.3274 1878.6921\n",
      " 1937.5836 1844.6576 1792.8875], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.87323   67.93326   77.163345  78.40315   72.70186   78.6191\n",
      "  80.29411  123.26902   71.98551   75.502   ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[42.500355 24.915089 33.056473 28.12263  32.07076  31.201859 23.46788\n",
      " 25.363073 44.604683 31.634619], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.32635 321.33047 422.92123 444.83295 400.68002 391.55844 469.68292\n",
      " 424.4059  445.78622 645.18665], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1695.1156   953.82043 1017.5875  1008.9701   969.95966 1023.58154\n",
      " 1103.6844  1068.0476   961.2289  1016.9674 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.6862  237.56465 228.08586 229.37578 227.88797 225.75504 242.99057\n",
      " 227.97876 256.11572 231.82222], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.28633 209.44717 249.18542 209.39445 209.25296 223.38232 210.78284\n",
      " 210.02466 209.16931 211.21782], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[868.94617 677.5712  690.9754  894.2323  679.95624 684.91614 676.35846\n",
      " 679.04846 671.4646  654.1269 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.91016 284.69513 284.79852 284.6805  287.47617 285.77792 284.76062\n",
      " 309.48593 324.84616 307.62076], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.2312   759.9032   800.88715  759.86975  789.0294   783.11475\n",
      " 1233.9807   793.1996   825.05164  815.6256 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2629.189  1860.2828 1839.4597 1863.6018 1857.9382 1851.4082 1878.5762\n",
      " 1937.0277 1844.8164 1793.4603], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.857834  67.94835   77.161804  78.39206   72.72464   78.606094\n",
      "  80.26256  122.55101   72.01091   75.51094 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[42.325497 24.938364 33.02413  28.13242  32.050655 31.19051  23.492214\n",
      " 25.385117 44.3966   31.61916 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.3581  321.6369  422.47015 444.09244 400.52228 391.5097  468.60822\n",
      " 423.93536 445.03296 641.59076], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1685.2408   954.0911  1017.41943 1008.90283  970.1422  1023.3351\n",
      " 1102.4021  1067.2275   961.45984 1016.807  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.68063 237.38773 228.07578 229.3461  227.88025 225.75508 242.71194\n",
      " 227.97002 255.63416 231.75015], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.24963 209.43796 248.672   209.39165 209.24863 223.05473 210.74081\n",
      " 210.00113 209.1689  211.194  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[867.2643  677.6442  690.9408  892.2791  680.0029  684.92175 676.44543\n",
      " 679.1048  671.60455 654.38684], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.9037  284.69635 284.80014 284.6805  287.45462 285.73862 284.7623\n",
      " 309.20624 324.37347 307.05655], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.2632   760.0768   800.85156  760.04333  789.0745   783.1928\n",
      " 1227.2498   793.2197   824.6984   815.4006 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2621.3013 1860.2887 1839.6781 1863.5846 1857.9603 1851.4886 1878.4607\n",
      " 1936.4752 1844.9739 1794.0348], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.842476  67.963936  77.16024   78.381     72.74737   78.59311\n",
      "  80.231125 121.83983   72.03629   75.51983 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[42.151924 24.961645 32.991924 28.14217  32.030617 31.179188 23.516666\n",
      " 25.407156 44.19011  31.60374 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.38974 321.94385 422.0213  443.3559  400.36508 391.46103 467.53986\n",
      " 423.46704 444.28384 638.0238 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1675.4528   954.36115 1017.2516  1008.83563  970.32404 1023.08923\n",
      " 1101.1271  1066.4116   961.69006 1016.64734], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.67508 237.21269 228.06575 229.3166  227.87256 225.75522 242.43645\n",
      " 227.96127 255.1578  231.67871], shape=(10,), dtype=float32)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(\n",
      "[212.21329 209.42896 248.16333 209.38892 209.24442 222.7319  210.6995\n",
      " 209.97794 209.16841 211.17036], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[865.5934  677.71716 690.9064  890.3392  680.0495  684.9274  676.53235\n",
      " 679.161   671.74445 654.64813], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.89728 284.6975  284.80182 284.6806  287.43323 285.70016 284.76398\n",
      " 308.92896 323.90506 306.50104], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.29504  760.2506   800.816    760.2172   789.1192   783.27057\n",
      " 1220.5852   793.2396   824.34717  815.17664], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2613.4712 1860.2936 1839.8971 1863.5676 1857.982  1851.5691 1878.346\n",
      " 1935.925  1845.1311 1794.612 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.82716   67.98001   77.158676  78.36994   72.77007   78.58016\n",
      "  80.19981  121.13544   72.06165   75.528694], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.97962  24.984936 32.959858 28.151882 32.010643 31.167889 23.541224\n",
      " 25.429184 43.985207 31.58837 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.42123 322.25122 421.57452 442.62338 400.2085  391.41254 466.47803\n",
      " 423.00098 443.53876 634.48566], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1665.7507   954.6307  1017.08466 1008.76855  970.5057  1022.8444\n",
      " 1099.8586  1065.5997   961.9199  1016.4881 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.66953 237.0395  228.05576 229.28731 227.8649  225.75546 242.16402\n",
      " 227.95255 254.68672 231.60794], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.17728 209.42004 247.65952 209.38623 209.24023 222.41382 210.65881\n",
      " 209.95511 209.16794 211.14697], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[863.9335  677.78986 690.8722  888.41223 680.0959  684.93317 676.619\n",
      " 679.21716 671.88416 654.9105 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.8909  284.6988  284.80347 284.6808  287.41202 285.66254 284.7657\n",
      " 308.6541  323.44073 305.95413], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.3267   760.42474  800.78064  760.39124  789.1638   783.34827\n",
      " 1213.9861   793.2594   823.99756  814.9537 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2605.6997 1860.2988 1840.1146 1863.5508 1858.0039 1851.6494 1878.2311\n",
      " 1935.377  1845.2883 1795.1908], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.811874  67.99657   77.1571    78.35891   72.79274   78.56724\n",
      "  80.16862  120.43778   72.087006  75.53751 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.808582 25.008234 32.927917 28.16155  31.990747 31.156612 23.565893\n",
      " 25.451199 43.781868 31.573034], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.45255 322.55902 421.12988 441.89478 400.05246 391.36407 465.42255\n",
      " 422.5371  442.7978  630.9761 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1656.1344   954.89954 1016.91797 1008.7018   970.6864  1022.6006\n",
      " 1098.5975  1064.7917   962.1494  1016.32947], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.66403 236.86813 228.0458  229.25822 227.85727 225.75583 241.89468\n",
      " 227.9439  254.22086 231.5378 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.1416  209.4113  247.16045 209.3835  209.23616 222.10051 210.61874\n",
      " 209.93266 209.16748 211.12378], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[862.2845  677.8626  690.83813 886.49835 680.14233 684.93896 676.70544\n",
      " 679.27313 672.0238  655.1743 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.88458 284.70007 284.8051  284.68103 287.39093 285.62573 284.7674\n",
      " 308.38165 322.98062 305.41583], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.35834  760.599    800.74524  760.5657   789.2084   783.42566\n",
      " 1207.4529   793.279    823.6498   814.7316 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2597.9854 1860.3041 1840.3328 1863.5344 1858.0256 1851.7295 1878.1172\n",
      " 1934.8317 1845.4453 1795.7719], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.796646  68.013596  77.1555    78.347916  72.81538   78.55434\n",
      "  80.13756  119.746826  72.11233   75.54628 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.6388   25.031536 32.89611  28.171183 31.970905 31.14536  23.590672\n",
      " 25.473204 43.580105 31.557749], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.48373 322.86725 420.68726 441.17017 399.89697 391.3158  464.37344\n",
      " 422.0755  442.06085 627.49493], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1646.6029   955.16797 1016.75195 1008.6351   970.8672  1022.3574\n",
      " 1097.3433  1063.9875   962.37805 1016.17126], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.65852 236.69865 228.03592 229.22934 227.84966 225.7563  241.62837\n",
      " 227.9353  253.7601  231.4683 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.10623 209.40274 246.6661  209.38086 209.23215 221.79182 210.57938\n",
      " 209.9106  209.16707 211.10078], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[860.6466 677.935  690.8043 884.5975 680.1886 684.9447 676.7919 679.3291\n",
      " 672.1632 655.4392], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.87827 284.70142 284.8068  284.68134 287.37003 285.58972 284.76913\n",
      " 308.11163 322.5246  304.886  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.3898   760.77344  800.71     760.7403   789.25256  783.50287\n",
      " 1200.984    793.29865  823.3039   814.5106 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2590.3286 1860.3092 1840.55   1863.5176 1858.0472 1851.8096 1878.0033\n",
      " 1934.2891 1845.6018 1796.3547], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.78145   68.03111   77.15388   78.336914  72.83797   78.54147\n",
      "  80.10658  119.062546  72.13764   75.555016], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.47027  25.054844 32.86444  28.180775 31.951136 31.134136 23.615551\n",
      " 25.4952   43.379898 31.542505], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.5147  323.17596 420.24683 440.44952 399.7421  391.26758 463.33066\n",
      " 421.61612 441.32794 624.042  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1637.156    955.43585 1016.58655 1008.5685   971.0472  1022.11536\n",
      " 1096.096   1063.1875   962.6061  1016.0137 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.65305 236.53096 228.02605 229.20065 227.84209 225.7568  241.36507\n",
      " 227.92668 253.30447 231.39946], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.0712  209.39424 246.17651 209.37817 209.22812 221.48772 210.5406\n",
      " 209.88884 209.16658 211.07803], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[859.01953 678.00745 690.77045 882.7095  680.2348  684.95056 676.87805\n",
      " 679.3848  672.30255 655.7054 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.87198 284.70282 284.80844 284.68176 287.34927 285.55453 284.7709\n",
      " 307.84387 322.07266 304.3647 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.4211   760.94824  800.67474  760.91504  789.29675  783.5799\n",
      " 1194.5798   793.318    822.9598   814.29065], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2582.7288 1860.3151 1840.7668 1863.5013 1858.0691 1851.889  1877.8903\n",
      " 1933.7487 1845.7578 1796.9395], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.7663    68.04909   77.152245  78.32594   72.860535  78.52864\n",
      "  80.07577  118.38484   72.162926  75.563705], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.302986 25.078156 32.832905 28.190323 31.931433 31.122936 23.640537\n",
      " 25.517178 43.181236 31.527304], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.54556 323.48502 419.8084  439.73273 399.58774 391.21945 462.29425\n",
      " 421.15894 440.59903 620.6172 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1627.7932   955.703   1016.4217  1008.5021   971.22656 1021.8742\n",
      " 1094.8556  1062.3912   962.8338  1015.85675], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.64755 236.36508 228.0162  229.17221 227.83455 225.75745 241.10478\n",
      " 227.91814 252.85397 231.3312 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.03645 209.38594 245.69156 209.37556 209.22424 221.18831 210.50244\n",
      " 209.86746 209.16617 211.05545], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[857.403   678.0796  690.73694 880.83435 680.2809  684.9564  676.96405\n",
      " 679.44055 672.4418  655.9727 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.86578 284.70422 284.81012 284.68222 287.32867 285.52014 284.77264\n",
      " 307.57852 321.62485 303.85168], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.4523   761.1231   800.6396   761.0901   789.3408   783.6566\n",
      " 1188.2394   793.33734  822.6175   814.07166], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2575.1853 1860.3207 1840.9836 1863.485  1858.0911 1851.9685 1877.7777\n",
      " 1933.2112 1845.9135 1797.5266], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.751175  68.067535  77.1506    78.315     72.883064  78.51584\n",
      "  80.04506  117.713745  72.18819   75.57235 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[41.136932 25.101467 32.80149  28.199833 31.911793 31.11176  23.66562\n",
      " 25.539146 42.984108 31.51215 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.57623 323.7945  419.37216 439.01996 399.43396 391.17145 461.264\n",
      " 420.70395 439.87402 617.2202 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1618.5138   955.96985 1016.25714 1008.4359   971.40546 1021.6338\n",
      " 1093.6218  1061.5989   963.06085 1015.7    ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.64214 236.20097 228.00644 229.14392 227.82706 225.75815 240.84749\n",
      " 227.90962 252.40852 231.26358], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[212.00204 209.37772 245.21127 209.37297 209.22043 220.8934  210.46494\n",
      " 209.84644 209.16573 211.03311], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[855.79755 678.1517  690.70355 878.972   680.32684 684.9623  677.0499\n",
      " 679.49615 672.5807  656.2412 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.85962 284.70566 284.81183 284.6828  287.30823 285.48654 284.77444\n",
      " 307.31555 321.18106 303.34702], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.48334  761.2982   800.6046   761.2652   789.3845   783.7332\n",
      " 1181.9625   793.3567   822.277    813.85376], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2567.6985 1860.3259 1841.1998 1863.469  1858.1125 1852.0481 1877.6656\n",
      " 1932.6755 1846.069  1798.1149], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.73611   68.08644   77.14894   78.304085  72.905556  78.50305\n",
      "  80.01447  117.04917   72.21343   75.58095 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.97211  25.124783 32.770214 28.209301 31.892218 31.10061  23.690804\n",
      " 25.561098 42.788513 31.497034], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.60675 324.10434 418.93793 438.31097 399.28073 391.1236  460.24005\n",
      " 420.25116 439.15314 613.851  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1609.3174   956.23596 1016.09357 1008.36975  971.584   1021.3944\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1092.3951  1060.8105   963.2873  1015.54395], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.63669 236.0387  227.99673 229.11588 227.81958 225.75899 240.59317\n",
      " 227.90117 251.96811 231.19658], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.96799 209.36967 244.7356  209.3704  209.21664 220.60306 210.42801\n",
      " 209.82576 209.16528 211.01096], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[854.2025  678.2236  690.67035 877.1224  680.37286 684.9682  677.13574\n",
      " 679.5515  672.7196  656.51086], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.85352 284.70718 284.81354 284.6834  287.28793 285.45374 284.7762\n",
      " 307.0549  320.74127 302.85065], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.5141   761.4735   800.5696   761.44055  789.4281   783.8095\n",
      " 1175.7491   793.37585  821.9381   813.6368 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2560.2676 1860.3318 1841.415  1863.4531 1858.1344 1852.1272 1877.5541\n",
      " 1932.143  1846.2239 1798.7054], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.72106   68.10579   77.14726   78.29317   72.928     78.49031\n",
      "  79.98401  116.39109   72.23866   75.589516], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.80851  25.148098 32.739075 28.218729 31.872711 31.089481 23.716085\n",
      " 25.583036 42.594444 31.481964], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.63712 324.41455 418.5058  437.6059  399.12808 391.07578 459.22226\n",
      " 419.8006  438.43613 610.50946], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1600.2034   956.50146 1015.9303  1008.3037   971.7621  1021.15576\n",
      " 1091.1752  1060.0261   963.51337 1015.38855], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.6313  235.87817 227.98706 229.08798 227.81213 225.75989 240.34177\n",
      " 227.8927  251.53267 231.13017], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.9342  209.36174 244.26448 209.36784 209.21297 220.31721 210.39172\n",
      " 209.80545 209.16489 210.98901], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[852.6185  678.2955  690.63727 875.28546 680.41864 684.9741  677.22125\n",
      " 679.6068  672.8583  656.7818 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.84747 284.7087  284.81525 284.6841  287.2678  285.4217  284.778\n",
      " 306.79654 320.3055  302.3625 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.5449   761.649    800.53467  761.6163   789.4716   783.88556\n",
      " 1169.5986   793.3949   821.60095  813.42084], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2552.892  1860.3376 1841.6302 1863.4373 1858.1562 1852.2064 1877.4426\n",
      " 1931.6125 1846.3789 1799.2981], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.70606   68.1256    77.14556   78.282295  72.950424  78.47759\n",
      "  79.95366  115.73944   72.263855  75.59804 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.64613  25.171413 32.70806  28.228119 31.853268 31.078379 23.741459\n",
      " 25.604956 42.401882 31.466934], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.6673  324.72513 418.07578 436.9048  398.976   391.02814 458.21063\n",
      " 419.35214 437.72308 607.19543], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1591.1719   956.7665  1015.76746 1008.2378   971.93945 1020.91815\n",
      " 1089.9619  1059.2454   963.73865 1015.2335 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.6259  235.7194  227.97739 229.06033 227.80469 225.7609  240.09329\n",
      " 227.88428 251.1022  231.0644 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.90079 209.35397 243.798   209.36531 209.20927 220.03586 210.35603\n",
      " 209.78545 209.16447 210.96725], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[851.04474 678.36707 690.60443 873.4611  680.4644  684.9801  677.3066\n",
      " 679.66205 672.99695 657.0536 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.8414  284.71027 284.81696 284.68488 287.24783 285.39044 284.77985\n",
      " 306.5405  319.87378 301.88242], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.57544  761.82465  800.4999   761.79205  789.51495  783.9615\n",
      " 1163.5106   793.4139   821.2658   813.20593], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2545.5725 1860.3434 1841.8451 1863.4211 1858.178  1852.2849 1877.3324\n",
      " 1931.0847 1846.533  1799.8926], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.69109   68.14586   77.14387   78.271416  72.972786  78.4649\n",
      "  79.92344  115.0942    72.28903   75.60651 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.484962 25.194729 32.677177 28.237463 31.833889 31.067297 23.766928\n",
      " 25.626862 42.210827 31.45195 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.69733 325.03604 417.64777 436.20737 398.8245  390.98056 457.20526\n",
      " 418.90594 437.014   603.9086 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1582.2214   957.03076 1015.60535 1008.1722   972.1164  1020.68146\n",
      " 1088.7556  1058.4686   963.9635  1015.0789 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.62053 235.56241 227.96785 229.03284 227.79733 225.76201 239.84775\n",
      " 227.8759  250.6766  230.99927], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.86765 209.34631 243.33601 209.36282 209.20569 219.75887 210.321\n",
      " 209.76582 209.16403 210.94576], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[849.48175 678.4385  690.5717  871.64923 680.51    684.9861  677.3919\n",
      " 679.7173  673.1354  657.3266 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.8354  284.71185 284.81866 284.6857  287.22797 285.35995 284.78165\n",
      " 306.28677 319.44595 301.41046], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.606    762.0005   800.4651   761.9678   789.5581   784.03723\n",
      " 1157.4845   793.4326   820.9321   812.9918 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2538.308  1860.3492 1842.0596 1863.4059 1858.1998 1852.3639 1877.222\n",
      " 1930.5592 1846.6873 1800.488 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.67617   68.16654   77.142136  78.260574  72.995125  78.45224\n",
      "  79.893326 114.455345  72.31418   75.614944], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.324993 25.218039 32.646423 28.246769 31.814575 31.05624  23.79249\n",
      " 25.648746 42.02127  31.437006], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.7272  325.34726 417.22183 435.51385 398.6735  390.93307 456.206\n",
      " 418.46182 436.30884 600.6489 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1573.352    957.29443 1015.44385 1008.10675  972.29266 1020.44543\n",
      " 1087.5558  1057.6956   964.1876  1014.925  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.61519 235.40714 227.95828 229.00557 227.78995 225.76318 239.60507\n",
      " 227.86758 250.25598 230.93472], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.83481 209.33879 242.87857 209.36035 209.2022  219.48633 210.28647\n",
      " 209.7465  209.16362 210.9244 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[847.9291  678.5099  690.5391  869.8499  680.55566 684.9921  677.4769\n",
      " 679.7723  673.2736  657.60077], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.82944 284.71353 284.8204  284.68658 287.2083  285.33023 284.78348\n",
      " 306.03528 319.02206 300.94647], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.6363   762.17645  800.4304   762.1439   789.60095  784.11255\n",
      " 1151.5199   793.45135  820.60046  812.77893], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2531.0981 1860.3549 1842.2734 1863.3903 1858.2214 1852.4421 1877.1123\n",
      " 1930.0369 1846.8408 1801.0859], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.6613   68.18767  77.1404   78.24974  73.01741  78.43959  79.86333\n",
      " 113.8228   72.33931  75.62333], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.166218 25.241346 32.615803 28.256027 31.795324 31.045208 23.818138\n",
      " 25.670612 41.8332   31.4221  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.7569  325.65884 416.79794 434.82413 398.52307 390.88568 455.2128\n",
      " 418.01987 435.6075  597.4162 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1564.5632   957.55774 1015.2827  1008.0414   972.46857 1020.21045\n",
      " 1086.3629  1056.9265   964.4113  1014.7715 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.60982 235.25357 227.94878 228.97852 227.78264 225.76445 239.36528\n",
      " 227.8593  249.84021 230.87076], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.80232 209.33145 242.42554 209.35786 209.19873 219.21817 210.25261\n",
      " 209.72754 209.16321 210.90327], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[846.387   678.58105 690.5068  868.0631  680.6011  684.9982  677.5619\n",
      " 679.8271  673.4116  657.876  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.82355 284.71524 284.82217 284.6876  287.18878 285.30127 284.78534\n",
      " 305.78604 318.60205 300.49048], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.66656  762.3526   800.396    762.3202   789.64374  784.18787\n",
      " 1145.6166   793.47003  820.2703   812.56683], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2523.9434 1860.3606 1842.487  1863.375  1858.2432 1852.5205 1877.0027\n",
      " 1929.5164 1846.9941 1801.6853], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.646454  68.20921   77.13864   78.238945  73.03966   78.42699\n",
      "  79.83345  113.19655   72.364395  75.63167 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[40.008636 25.264648 32.585304 28.26525  31.776142 31.034199 23.843876\n",
      " 25.692465 41.6466   31.407242], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.78644 325.9707  416.37607 434.13818 398.37323 390.83844 454.22568\n",
      " 417.58014 434.9101  594.21027], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1555.8544   957.8202  1015.12225 1007.9761   972.6439  1019.9762\n",
      " 1085.1765  1056.1611   964.6344  1014.61865], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.60446 235.10173 227.9393  228.95161 227.7753  225.7658  239.12833\n",
      " 227.85103 249.42924 230.80742], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.7701  209.32417 241.977   209.35542 209.19536 218.95432 210.21928\n",
      " 209.70894 209.16281 210.8823 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[844.8553  678.65216 690.4745  866.28845 680.6465  685.0043  677.6466\n",
      " 679.88196 673.5496  658.15216], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.81772 284.71695 284.82388 284.68863 287.16937 285.27307 284.78717\n",
      " 305.53906 318.18597 300.0423 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.69653  762.5289   800.3614   762.4965   789.6864   784.2628\n",
      " 1139.7742   793.48846  819.9421   812.3558 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2516.8423 1860.3666 1842.7    1863.3597 1858.2653 1852.5986 1876.8943\n",
      " 1928.9984 1847.1471 1802.2859], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.631645  68.231186  77.13687   78.228165  73.06187   78.41441\n",
      "  79.8037   112.57652   72.389465  75.63998 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.852234 25.287947 32.554935 28.274426 31.757025 31.023214 23.869696\n",
      " 25.714289 41.461475 31.392426], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.8158  326.28284 415.95624 433.45605 398.2239  390.79132 453.24463\n",
      " 417.1425  434.21655 591.03094], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1547.2252   958.0825  1014.9624  1007.91113  972.81885 1019.743\n",
      " 1083.9967  1055.3998   964.85693 1014.4662 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.59915 234.95161 227.92989 228.92496 227.76804 225.76724 238.8942\n",
      " 227.8428  249.02307 230.74463], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.73819 209.31706 241.53287 209.35303 209.19199 218.69475 210.18657\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 209.6906  209.1624  210.86157], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[843.33386 678.7231  690.4425  864.5262  680.6918  685.0104  677.7313\n",
      " 679.9366  673.6874  658.42944], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.81186 284.7187  284.82565 284.68976 287.15018 285.24554 284.78906\n",
      " 305.29437 317.77374 299.602  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.7264   762.70526  800.32697  762.673    789.7288   784.33777\n",
      " 1133.992    793.5067   819.61536  812.1457 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2509.7952 1860.3727 1842.9127 1863.3447 1858.2871 1852.6765 1876.7859\n",
      " 1928.4828 1847.3    1802.8887], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.616875  68.253586  77.135086  78.21739   73.08404   78.401855\n",
      "  79.77406  111.96271   72.4145    75.648224], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.69701  25.311237 32.5247   28.283564 31.73797  31.012253 23.895601\n",
      " 25.736095 41.277813 31.37765 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.84503 326.59525 415.53842 432.77774 398.07513 390.7443  452.26953\n",
      " 416.70697 433.52686 587.8781 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1538.6747   958.34375 1014.8029  1007.8462   972.9933  1019.5106\n",
      " 1082.8237  1054.6418   965.07874 1014.3143 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.59387 234.80313 227.9205  228.89847 227.76079 225.76875 238.66284\n",
      " 227.83456 248.6217  230.68246], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.70657 209.31009 241.09314 209.35062 209.18872 218.43948 210.15446\n",
      " 209.67264 209.16206 210.84102], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[841.82275 678.7938  690.4107  862.776   680.73694 685.0165  677.8157\n",
      " 679.9912  673.82495 658.70764], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.8061  284.72052 284.8274  284.69092 287.13104 285.2188  284.79095\n",
      " 305.05182 317.3653  299.16946], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.75616  762.8818   800.29254  762.84973  789.771    784.41223\n",
      " 1128.2698   793.525    819.2905   811.93677], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2502.8022 1860.3785 1843.1252 1863.3297 1858.3088 1852.7545 1876.6781\n",
      " 1927.9697 1847.4521 1803.4929], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.60216   68.27638   77.133286  78.20665   73.106155  78.389336\n",
      "  79.744545 111.35506   72.4395    75.65645 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.542957 25.334522 32.494587 28.292658 31.718975 31.001312 23.921589\n",
      " 25.75788  41.095604 31.362915], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.87408 326.90796 415.12265 432.10312 397.92694 390.69733 451.30045\n",
      " 416.27362 432.8409  584.75165], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1530.2032   958.6044  1014.64435 1007.78156  973.1672  1019.279\n",
      " 1081.6571  1053.8877   965.3     1014.1629 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.5886  234.65637 227.91118 228.87212 227.75357 225.77036 238.4343\n",
      " 227.82645 248.22505 230.6209 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.67525 209.30318 240.6578  209.34827 209.18555 218.18843 210.1229\n",
      " 209.655   209.16167 210.82068], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[840.3218  678.86444 690.3789  861.0381  680.7821  685.02264 677.89996\n",
      " 680.0457  673.9624  658.9869 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.80035 284.72232 284.82916 284.6922  287.11212 285.1928  284.79282\n",
      " 304.8115  316.96075 298.74463], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.78577  763.0585   800.25836  763.0264   789.81323  784.48645\n",
      " 1122.6073   793.5432   818.9674   811.7285 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2495.862  1860.3848 1843.3373 1863.3148 1858.3307 1852.832  1876.5713\n",
      " 1927.459  1847.6041 1804.0986], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.58746   68.2996    77.13146   78.19593   73.12824   78.37684\n",
      "  79.71515  110.75352   72.464485  75.66461 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.390064 25.357798 32.464603 28.301706 31.700047 30.990398 23.947653\n",
      " 25.779642 40.914837 31.348225], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.90295 327.2209  414.7089  431.43222 397.77924 390.65048 450.3373\n",
      " 415.84238 432.15894 581.65125], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1521.8092   958.86475 1014.486   1007.7169   973.3402  1019.04846\n",
      " 1080.4972  1053.1376   965.5209  1014.01184], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.58334 234.51128 227.9019  228.84602 227.74641 225.77205 238.20854\n",
      " 227.81831 247.83304 230.55989], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.64424 209.29643 240.22672 209.34592 209.18234 217.9416  210.09192\n",
      " 209.6377  209.16129 210.8005 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[838.8312  678.93494 690.3475  859.312   680.827   685.02893 677.98413\n",
      " 680.0999  674.0996  659.2671 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.79465 284.7242  284.83093 284.6935  287.09332 285.16754 284.79474\n",
      " 304.57343 316.55997 298.32742], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.8153  763.2353  800.2241  763.2033  789.8551  784.5606 1117.0042\n",
      "  793.5613  818.6458  811.5215], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2488.975  1860.3909 1843.5485 1863.3002 1858.3525 1852.9095 1876.4639\n",
      " 1926.9509 1847.7559 1804.7058], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.572815  68.32322   77.12962   78.18522   73.15027   78.36438\n",
      "  79.68587  110.15806   72.489426  75.67273 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.23833  25.381062 32.434746 28.31071  31.68118  30.979502 23.973797\n",
      " 25.801386 40.735504 31.333569], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.9317  327.5341  414.29706 430.76505 397.63217 390.60373 449.38013\n",
      " 415.41327 431.48065 578.577  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1513.4929   959.124   1014.328   1007.65265  973.51306 1018.8187\n",
      " 1079.3435  1052.3911   965.7409  1013.8617 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.57808 234.36783 227.89265 228.82011 227.73923 225.77383 237.9855\n",
      " 227.81023 247.44576 230.49947], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.61357 209.28984 239.80002 209.3436  209.17928 217.69893 210.0615\n",
      " 209.62068 209.16089 210.78056], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[837.3507  679.0053  690.31604 857.59845 680.8721  685.0351  678.068\n",
      " 680.1542  674.2367  659.5482 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.789   284.7261  284.8327  284.6949  287.0747  285.14297 284.7967\n",
      " 304.33746 316.16293 297.91782], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.8446   763.4122   800.19006  763.3803   789.8968   784.6344\n",
      " 1111.4597   793.5792   818.32605  811.31525], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2482.141  1860.3971 1843.7598 1863.2858 1858.3746 1852.9866 1876.3578\n",
      " 1926.4451 1847.907  1805.3147], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.5582    68.347244  77.12778   78.17454   73.17226   78.35193\n",
      "  79.65669  109.56865   72.51434   75.68082 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[39.08775  25.404316 32.405014 28.319677 31.662374 30.968634 24.000015\n",
      " 25.823095 40.557606 31.31896 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.96027 327.84747 413.88736 430.10156 397.4856  390.5571  448.4288\n",
      " 414.98624 430.80615 575.5286 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1505.2539   959.38293 1014.1708  1007.5881   973.68524 1018.58966\n",
      " 1078.1968  1051.6483   965.96045 1013.71173], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.57285 234.226   227.88345 228.79439 227.73213 225.77568 237.76518\n",
      " 227.80215 247.06311 230.4396 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.58313 209.28336 239.3776  209.34131 209.17627 217.4604  210.03162\n",
      " 209.604   209.16052 210.76077], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[835.88007 679.0755  690.2848  855.8966  680.9169  685.0413  678.15173\n",
      " 680.2082  674.37354 659.83026], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.7834  284.72803 284.8345  284.69635 287.05618 285.11908 284.79858\n",
      " 304.1037  315.76962 297.51572], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 791.87366  763.58923  800.1559   763.5574   789.9384   784.7081\n",
      " 1105.9738   793.5969   818.008    811.11005], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2475.3599 1860.4036 1843.9703 1863.2715 1858.3965 1853.0635 1876.2517\n",
      " 1925.9421 1848.058  1805.9252], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.54362   68.37166   77.1259    78.16387   73.1942    78.33952\n",
      "  79.62763  108.98523   72.539215  75.68886 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[38.938313 25.42756  32.37541  28.328598 31.643637 30.957785 24.026308\n",
      " 25.844784 40.381123 31.304388], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[380.98862 328.1611  413.47958 429.4419  397.33957 390.51056 447.4834\n",
      " 414.56128 430.1355  572.5059 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1497.0914   959.64124 1014.01434 1007.52405  973.8568  1018.36163\n",
      " 1077.0563  1050.9092   966.1795  1013.5624 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.56763 234.08585 227.8743  228.7688  227.725   225.77759 237.54756\n",
      " 227.79414 246.68501 230.38034], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.55298 209.27698 238.95943 209.33902 209.17326 217.22595 210.0024\n",
      " 209.58765 209.16011 210.74117], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[834.4196  679.1456  690.2539  854.20654 680.9617  685.0477  678.23535\n",
      " 680.26227 674.51025 660.1133 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.7778  284.73    284.83627 284.69785 287.03778 285.09598 284.80054\n",
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      "[ 78.52909   68.396454  77.12401   78.15321   73.216095  78.32713\n",
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      " 25.866446 40.206055 31.289862], shape=(10,), dtype=float32)\n",
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      "[285.77228 284.73203 284.83807 284.69943 287.0196  285.07355 284.8025\n"
     ]
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      " 1084.6063   793.66705  816.7524   810.29865], shape=(10,), dtype=float32)\n",
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      "[ 78.48568   68.47314   77.11824   78.12139   73.2815    78.29014\n",
      "  79.512566 106.71078   72.638374  75.720535], shape=(10,), dtype=float32)\n",
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      "tf.Tensor(\n",
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      " 412.8824  427.49005 560.66907], shape=(10,), dtype=float32)\n",
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      " 227.76236 245.21814 230.14885], shape=(10,), dtype=float32)\n",
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      "[211.43542 209.25273 237.32877 209.33011 209.1619  216.32857 209.89067\n",
      " 209.52527 209.15869 210.66467], shape=(10,), dtype=float32)\n",
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      "[828.67725 679.42426 690.1315  847.5648  681.13965 685.07306 678.568\n",
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      " 302.96686 313.85846 295.61606], shape=(10,), dtype=float32)\n",
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      "[ 792.0174   764.47546  799.98663  764.44415  790.1436   785.0729\n",
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      "[ 78.4713    68.49946   77.11629   78.11082   73.30321   78.27785\n",
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      " 412.46786 426.83798 557.77264], shape=(10,), dtype=float32)\n",
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      " 209.51047 209.15837 210.64604], shape=(10,), dtype=float32)\n",
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      "[827.2661  679.4936  690.1013  845.9336  681.184   685.0795  678.65076\n",
      " 680.53046 675.19104 661.54144], shape=(10,), dtype=float32)\n",
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      "[ 792.04565  764.65283  799.9531   764.6218   790.1842   785.1451\n",
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      "[ 78.45695   68.52613   77.11432   78.10026   73.32486   78.2656\n",
      "  79.45571  105.608505  72.68774   75.7361  ], shape=(10,), dtype=float32)\n",
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      "tf.Tensor(\n",
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      " 412.05533 426.18954 554.901  ], shape=(10,), dtype=float32)\n",
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      " 1070.3478  1046.5521   967.48047 1012.67706], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 227.74667 244.51152 230.03642], shape=(10,), dtype=float32)\n",
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      " 209.49594 209.15804 210.62756], shape=(10,), dtype=float32)\n",
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      " 302.52686 313.11945 294.90677], shape=(10,), dtype=float32)\n",
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      "[ 792.07385  764.8304   799.91956  764.79944  790.2245   785.217\n",
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      "[ 78.44263   68.55315   77.11233   78.089714  73.346466  78.25337\n",
      "  79.42745  105.065994  72.71236   75.74382 ], shape=(10,), dtype=float32)\n",
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      "[37.923717 25.58985  32.17167  28.389812 31.5142   30.882486 24.21226\n",
      " 25.995829 39.184807 31.203537], shape=(10,), dtype=float32)\n",
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      " 411.64493 425.54477 552.05396], shape=(10,), dtype=float32)\n",
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      " 227.73889 244.16476 229.98105], shape=(10,), dtype=float32)\n",
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      " 209.48172 209.15767 210.60928], shape=(10,), dtype=float32)\n",
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      "[824.47327 679.6318  690.04144 842.70557 681.2723  685.09247 678.8158\n",
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      "tf.Tensor(\n",
      "[285.73996 284.74478 284.84903 284.71024 286.91324 284.9532  284.81445\n",
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      "[ 792.1018   765.0078   799.8861   764.97705  790.2645   785.2889\n",
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      "[ 78.42834   68.58055   77.11032   78.079216  73.368004  78.24118\n",
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      "tf.Tensor(\n",
      "[37.783195 25.612965 32.143055 28.398382 31.495953 30.871817 24.23907\n",
      " 26.017284 39.019386 31.189291], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
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      " 1068.1619  1045.129    967.9093  1012.38574], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.52649 233.02176 227.80249 228.57108 227.66914 225.7958  235.90181\n"
     ]
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     "output_type": "stream",
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      " 209.46782 209.15732 210.59119], shape=(10,), dtype=float32)\n",
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      "[823.0915  679.7006  690.01184 841.1089  681.3164  685.099   678.89795\n",
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      "[ 78.41411   68.608284  77.10831   78.06871   73.38951   78.229004\n",
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      " 26.038712 38.855316 31.175085], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 209.45418 209.15701 210.57321], shape=(10,), dtype=float32)\n",
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      "tf.Tensor(\n",
      "[ 792.1573   765.363    799.81946  765.3324   790.34436  785.43164\n",
      " 1054.2435   793.7687   814.91864  809.11   ], shape=(10,), dtype=float32)\n",
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      "[ 78.39989   68.63637   77.106255  78.05823   73.41096   78.21686\n",
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      "tf.Tensor(\n",
      "[37.505417 25.65913  32.086193 28.415379 31.45965  30.850544 24.292864\n",
      " 26.0601   38.692585 31.160915], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.26324 331.3064  409.50986 423.0438  395.90936 390.0508  438.34628\n",
      " 410.42584 423.63232 543.65936], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      "tf.Tensor(\n",
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      " 227.71577 243.15056 229.81815], shape=(10,), dtype=float32)\n",
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      "[211.2675  209.21997 235.00583 209.31741 209.1466  215.10022 209.73906\n",
      " 209.4408  209.15666 210.55547], shape=(10,), dtype=float32)\n",
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      " 680.79584 675.8668  662.9899 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.7243  284.7516  284.85458 284.71643 286.86197 284.902   284.82056\n",
      " 301.67145 311.68384 293.57233], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.1848   765.54065  799.7861   765.51013  790.384    785.5027\n",
      " 1049.3752   793.7852   814.6188   808.91516], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2404.1472 1860.4766 1846.2576 1863.1215 1858.6365 1853.9    1875.1189\n",
      " 1920.5621 1849.6946 1812.7242], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.38572   68.6648    77.1042    78.04775   73.43235   78.204735\n",
      "  79.31557  102.95237   72.81042   75.774216], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[37.36814  25.682178 32.05795  28.42381  31.44159  30.839941 24.31984\n",
      " 26.081457 38.531174 31.146786], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.28976 331.62152 409.12357 422.42368 395.76935 390.00537 437.46368\n",
      " 410.02353 423.0021  540.9094 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1412.2219   962.4403  1012.32654 1006.82794  975.7095  1015.90985\n",
      " 1064.9302  1043.0212   968.54785 1011.953  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.5113  232.64832 227.77625 228.49991 227.64865 225.8038  235.32698\n",
      " 227.70808 242.82104 229.76492], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.24052 209.21492 234.63269 209.31534 209.14421 214.90878 209.71567\n",
      " 209.42776 209.15634 210.53789], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[819.003   679.90625 689.9238  836.3866  681.4478  685.1189  679.14355\n",
      " 680.8486  676.00134 663.28186], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.71918 284.75397 284.8565  284.71863 286.84512 284.8862  284.82263\n",
      " 301.46268 311.33368 293.25592], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.21234  765.71826  799.753    765.68787  790.4232   785.57336\n",
      " 1044.5603   793.80164  814.3205   808.7211 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2397.974  1860.4838 1846.4629 1863.1084 1858.6588 1853.9752 1875.0186\n",
      " 1920.0869 1849.8414 1813.3492], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.37159   68.69356   77.10213   78.03731   73.45369   78.192635\n",
      "  79.28787  102.43789   72.83482   75.78169 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[37.23193  25.705204 32.029823 28.432194 31.423588 30.829357 24.346867\n",
      " 26.10278  38.371098 31.132696], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.3161  331.93677 408.7392  421.80704 395.62982 389.96005 436.58673\n",
      " 409.62323 422.37543 538.1835 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1404.9417   962.69073 1012.1763  1006.76544  975.8747  1015.6922\n",
      " 1063.8654  1042.3257   968.75946 1011.8097 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.50627 232.52681 227.76758 228.47652 227.64188 225.80661 235.14038\n",
      " 227.70047 242.49576 229.7122 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.21375 209.20999 234.26347 209.31332 209.14194 214.72112 209.69272\n",
      " 209.41501 209.15604 210.52048], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[817.65924 679.97455 689.89496 834.8351  681.4915  685.12555 679.22516\n",
      " 680.9012  676.1357  663.5745 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.7141  284.7563  284.85834 284.7209  286.82843 284.87103 284.8247\n",
      " 301.25583 310.9869  292.94626], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.2395   765.89594  799.71985  765.86566  790.4625   785.644\n",
      " 1039.7994   793.818    814.0238   808.5282 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2391.849  1860.4908 1846.6672 1863.0957 1858.6807 1854.0496 1874.9192\n",
      " 1919.614  1849.9875 1813.9756], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.35749   68.72264   77.10002   78.026886  73.474976  78.18057\n",
      "  79.26028  101.9289    72.85919   75.78912 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[37.096786 25.728205 32.00182  28.440533 31.405645 30.818798 24.373941\n",
      " 26.124063 38.21233  31.118649], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.3423  332.252   408.35675 421.1939  395.49088 389.91483 435.71515\n",
      " 409.2249  421.7523  535.4812 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1397.7316   962.9406  1012.0265  1006.70325  976.03925 1015.4752\n",
      " 1062.8065  1041.6339   968.9704  1011.6669 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.50125 232.40683 227.75896 228.4533  227.63513 225.8095  234.95618\n",
      " 227.69287 242.17468 229.66003], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.18726 209.20512 233.89815 209.31131 209.13965 214.53711 209.67024\n",
      " 209.40251 209.15572 210.50325], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[816.3248  680.0426  689.8661  833.29456 681.5351  685.1322  679.30646\n",
      " 680.9536  676.2698  663.86786], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.70905 284.7587  284.8602  284.7232  286.81186 284.85654 284.82678\n",
      " 301.05103 310.64362 292.6433 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.2666   766.0736   799.68677  766.04333  790.5017   785.7143\n",
      " 1035.0916   793.8341   813.72864  808.3361 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2385.7732 1860.4977 1846.8718 1863.0833 1858.7024 1854.1243 1874.82\n",
      " 1919.1438 1850.1332 1814.6028], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.34342   68.75206   77.0979    78.01648   73.4962    78.168526\n",
      "  79.23281  101.42538   72.88351   75.79651 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.96269  25.75118  31.973934 28.448822 31.387766 30.808258 24.401066\n",
      " 26.145313 38.05487  31.10464 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.36826 332.56732 407.97617 420.58417 395.3524  389.86972 434.84918\n",
      " 408.82867 421.13275 532.8026 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1390.5916   963.1898  1011.87744 1006.64124  976.2031  1015.2591\n",
      " 1061.7537  1040.9456   969.1808  1011.5247 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.49626 232.2883  227.75037 228.4303  227.62839 225.81242 234.77446\n",
      " 227.6853  241.85771 229.60837], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.16106 209.20036 233.53671 209.30933 209.13745 214.35678 209.64832\n",
      " 209.3903  209.15536 210.48616], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[814.9997  680.11053 689.8375  831.76495 681.5786  685.139   679.3876\n",
      " 681.0061  676.4038  664.16187], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.70404 284.76108 284.8621  284.72552 286.79547 284.84265 284.8289\n",
      " 300.84818 310.30365 292.34702], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.29364  766.2512   799.6538   766.2213   790.54047  785.78436\n",
      " 1030.436    793.8502   813.4352   808.1449 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2379.7454 1860.5052 1847.0756 1863.0709 1858.7242 1854.199  1874.7213\n",
      " 1918.676  1850.279  1815.2308], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.32939  68.7818   77.09578  78.00609  73.51738  78.1565   79.20546\n",
      " 100.92727  72.90778  75.80385], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.82965  25.77413  31.94617  28.457067 31.369946 30.797739 24.428234\n",
      " 26.166523 37.898705 31.090668], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.39413 332.8827  407.59747 419.97803 395.2145  389.82465 433.98868\n",
      " 408.4344  420.51678 530.14746], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1383.5211   963.4383  1011.7289  1006.5792   976.3666  1015.04376\n",
      " 1060.7073  1040.2607   969.39044 1011.38293], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.49129 232.17123 227.74182 228.40742 227.62167 225.81546 234.59517\n",
      " 227.67778 241.54495 229.55722], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.13509 209.19576 233.17917 209.30734 209.13535 214.18005 209.62686\n",
      " 209.37842 209.1551  210.46928], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[813.6839  680.17834 689.8091  830.24677 681.62195 685.1459  679.4686\n",
      " 681.05835 676.5374  664.45654], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.69904 284.76358 284.864   284.72797 286.7791  284.82935 284.83096\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 300.64728 309.9672  292.0573 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.3203   766.42883  799.6208   766.3989   790.5791   785.8542\n",
      " 1025.8334   793.86615  813.1434   807.9548 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2373.7656 1860.512  1847.2787 1863.0588 1858.7458 1854.2732 1874.623\n",
      " 1918.2102 1850.4242 1815.8597], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 78.3154    68.811844  77.09363   77.995705  73.5385    78.144516\n",
      "  79.1782   100.43455   72.93201   75.81114 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.697655 25.797049 31.918524 28.465271 31.352184 30.787241 24.455448\n",
      " 26.187698 37.743835 31.076733], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.41983 333.198   407.22073 419.3753  395.0771  389.77972 433.1336\n",
      " 408.04208 419.9043  527.5156 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1376.5198  963.6862 1011.5807 1006.5172  976.5295 1014.8296 1059.6667\n",
      " 1039.5793  969.5994 1011.2416], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.4863  232.05566 227.7333  228.38477 227.61504 225.81851 234.41826\n",
      " 227.67032 241.23625 229.50659], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.10938 209.19125 232.82544 209.30539 209.13322 214.00699 209.60587\n",
      " 209.36674 209.15479 210.45255], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[812.3774  680.246   689.78076 828.7394  681.66534 685.15265 679.54944\n",
      " 681.1105  676.6709  664.75183], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.69415 284.76605 284.8659  284.73044 286.763   284.81668 284.8331\n",
      " 300.44833 309.63397 291.7741 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.34686  766.6065   799.588    766.5767   790.61774  785.9237\n",
      " 1021.2826   793.882    812.8529   807.76526], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2367.8335 1860.5192 1847.4818 1863.0463 1858.7683 1854.3473 1874.5251\n",
      " 1917.7467 1850.569  1816.4899], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.30144  68.84222  77.09147  77.985344 73.559555 78.132545 79.151054\n",
      " 99.94716  72.95618  75.81838 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.5667   25.819942 31.890997 28.47342  31.334484 30.776764 24.4827\n",
      " 26.208832 37.590252 31.06284 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.4453  333.51337 406.8458  418.77597 394.94025 389.73492 432.28394\n",
      " 407.6518  419.29535 524.9069 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1369.5872  963.9334 1011.4332 1006.4557  976.6917 1014.6159 1058.6322\n",
      " 1038.9016  969.8078 1011.1007], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.48135 231.94148 227.72485 228.36223 227.60837 225.82161 234.24373\n",
      " 227.66281 240.93167 229.45645], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.08401 209.18686 232.4755  209.3035  209.13115 213.83743 209.58537\n",
      " 209.3554  209.15446 210.436  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[811.08014 680.3134  689.7527  827.243   681.7085  685.1595  679.6301\n",
      " 681.1625  676.8041  665.0477 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.68924 284.76855 284.86777 284.73297 286.74695 284.8046  284.8352\n",
      " 300.25134 309.30414 291.4974 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.3735   766.78394  799.55524  766.75433  790.65607  785.99304\n",
      " 1016.7834   793.89764  812.56433  807.57684], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2361.9495 1860.527  1847.6842 1863.0344 1858.7904 1854.4209 1874.428\n",
      " 1917.2858 1850.7133 1817.1208], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.28752 68.87289 77.08927 77.97501 73.58056 78.12059 79.12402 99.46509\n",
      " 72.9803  75.82558], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.436775 25.842804 31.863592 28.481525 31.316843 30.766315 24.509995\n",
      " 26.229925 37.437946 31.048985], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.47058 333.8287  406.4728  418.18018 394.80396 389.69012 431.4397\n",
      " 407.2635  418.68988 522.32135], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1362.7225   964.1797  1011.286   1006.3939   976.8535  1014.40314\n",
      " 1057.6038  1038.2272   970.0156  1010.9606 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.47641 231.82877 227.7164  228.33989 227.60176 225.82483 234.07158\n",
      " 227.65536 240.6311  229.40686], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.0588  209.18257 232.12935 209.30156 209.12915 213.67142 209.5654\n",
      " 209.34431 209.15417 210.41963], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[809.79205 680.3808  689.7248  825.7573  681.7516  685.1663  679.7106\n",
      " 681.2144  676.93713 665.34424], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.68436 284.77112 284.8697  284.73553 286.73105 284.79312 284.83734\n",
      " 300.05627 308.97763 291.22714], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.39996  766.9616   799.5225   766.932    790.6942   786.06213\n",
      " 1012.33575  793.9132   812.2771   807.38934], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2356.1123 1860.5345 1847.8857 1863.0222 1858.8118 1854.4949 1874.3317\n",
      " 1916.8269 1850.8577 1817.7526], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.27362  68.90386  77.08707  77.96468  73.60151  78.10869  79.09709\n",
      " 98.988266 73.00438  75.832726], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.307873 25.865635 31.836304 28.489584 31.299261 30.75587  24.537323\n",
      " 26.250977 37.286907 31.035168], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.49573 334.14398 406.10165 417.5877  394.66812 389.64548 430.60083\n",
      " 406.8771  418.08798 519.75867], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1355.926    964.4255  1011.1398  1006.33264  977.0145  1014.1913\n",
      " 1056.581   1037.5564   970.22266 1010.8207 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.47148 231.71748 227.70801 228.3177  227.59517 225.82808 233.90178\n",
      " 227.648   240.33452 229.35774], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.03394 209.17838 231.78694 209.29965 209.12723 213.50894 209.54585\n",
      " 209.3335  209.1539  210.40341], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[808.51306 680.448   689.697   824.28253 681.79456 685.1732  679.7907\n",
      " 681.26624 677.06995 665.6413 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.67953 284.77368 284.8716  284.7382  286.71527 284.78226 284.83948\n",
      " 299.8631  308.6544  290.96323], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[ 792.4259   767.1391   799.49     767.1095   790.7322   786.131\n",
      " 1007.9388   793.92865  811.9914   807.20276], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2350.3218 1860.5416 1848.0875 1863.0105 1858.8342 1854.5684 1874.2356\n",
      " 1916.3704 1851.0012 1818.385 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.25977  68.935135 77.084854 77.954384 73.62239  78.09679  79.07029\n",
      " 98.51671  73.0284   75.83981 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[36.179993 25.888437 31.809132 28.497595 31.281738 30.745459 24.564688\n",
      " 26.271988 37.137123 31.021387], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.5207  334.4593  405.73236 416.99863 394.53287 389.60095 429.76727\n",
      " 406.49274 417.48944 517.2186 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1349.1968   964.6704  1010.99365 1006.2715   977.1753  1013.98035\n",
      " 1055.5643  1036.8892   970.4291  1010.68146], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.4666  231.60757 227.69963 228.2957  227.58858 225.83139 233.7343\n",
      " 227.64062 240.04196 229.30913], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[211.00925 209.17432 231.44827 209.29782 209.12532 213.34993 209.52678\n",
      " 209.3229  209.15361 210.38736], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[807.2431  680.51495 689.6694  822.8185  681.8375  685.1802  679.8709\n",
      " 681.3179  677.2026  665.9391 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 403.85645 413.39606 500.06406], shape=(10,), dtype=float32)\n",
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      " 403.12054 412.25693 495.35953], shape=(10,), dtype=float32)\n",
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     ]
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      "tf.Tensor(\n",
      "[285.629   284.80377 284.89307 284.77054 286.55017 284.70013 284.86365\n",
      " 297.86057 305.31003 288.46445], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.7037  769.0867  799.13556 769.0587  791.137   786.87085 962.83154\n",
      " 794.0907  808.95154 805.2089 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2289.655  1860.6289 1850.2712 1862.8916 1859.0764 1855.366  1873.208\n",
      " 1911.4994 1852.5569 1825.3873], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.10966  69.29745  77.05913  77.842094 73.84804  77.96757  78.78241\n",
      " 93.664276 73.28907  75.9146  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.838978 26.136866 31.517939 28.582495 31.092834 30.632233 24.867538\n",
      " 26.500126 35.5706   30.872295], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 402.3923  411.13116 490.74033], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 1044.768   1029.7739   972.6564  1009.18176], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 227.5616  237.07817 228.80644], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.75452 209.13615 227.96147 209.27847 209.10767 211.82166 209.34705\n",
      " 209.22371 209.15071 210.22139], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 681.8787  678.64514 669.2464 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.62466 284.80667 284.89505 284.77374 286.53592 284.6959  284.8659\n",
      " 297.68936 305.02463 288.27258], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.7279  769.26306 799.10376 769.2353  791.1726  786.93665 959.01794\n",
      " 794.10486 808.6844  805.0331 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2284.4084 1860.6371 1850.467  1862.8815 1859.0986 1855.4373 1873.1176\n",
      " 1911.07   1852.6959 1826.0271], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.09621  69.33193  77.05666  77.831985 73.86816  77.955956 78.75688\n",
      " 93.252655 73.312416 75.92109 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.72288  26.15921  31.492153 28.589916 31.076    30.622059 24.895191\n",
      " 26.520573 35.435364 30.858963], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.80624 338.23544 401.44452 410.19034 392.95053 389.07373 420.17343\n",
      " 402.031   410.57324 488.4625 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
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      " 1043.821   1029.1475   972.8547  1009.0482 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.40878 230.39502 227.60239 228.04436 227.51176 225.87541 231.89995\n",
      " 227.55461 236.8311  228.76358], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.73282 209.13322 227.66556 209.27682 209.10628 211.70206 209.3333\n",
      " 209.21616 209.15048 210.20724], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.6959  681.3069  689.3522  806.06836 682.3456  685.2665  680.8174\n",
      " 681.9289  678.7748  669.5496 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.62027 284.80957 284.89703 284.777   286.5218  284.6922  284.86813\n",
      " 297.5199  304.74225 288.0864 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.7522  769.43933 799.0721  769.41174 791.2081  787.0021  955.2508\n",
      " 794.1185  808.4186  804.8579 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2279.2048 1860.6461 1850.6617 1862.8713 1859.1205 1855.5084 1873.0276\n",
      " 1910.6432 1852.8347 1826.6674], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.082794 69.366646 77.0542   77.82189  73.888214 77.94438  78.731445\n",
      " 92.84578  73.3357   75.927536], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.60774  26.181509 31.466486 28.597284 31.059229 30.611902 24.922853\n",
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      "tf.Tensor(\n",
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      "tf.Tensor(\n",
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      " 1042.8795  1028.5242   973.05225 1008.91534], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.4041  230.30252 227.59453 228.02446 227.50552 225.8794  231.76115\n",
      " 227.54764 236.58762 228.72116], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.71133 209.13045 227.373   209.27522 209.10501 211.58553 209.32002\n",
      " 209.20886 209.15024 210.19327], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[791.53986 681.3719  689.32684 804.73914 682.3873  685.27386 680.8951\n",
      " 681.9791  678.9042  669.85315], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.616   284.8125  284.899   284.78036 286.50775 284.68906 284.87042\n",
      " 297.35214 304.46286 287.90582], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.7762  769.6155  799.0404  769.5881  791.24335 787.06726 951.5295\n",
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      "tf.Tensor(\n",
      "[2274.0454 1860.6545 1850.8561 1862.8616 1859.1428 1855.5797 1872.9381\n",
      " 1910.218  1852.973  1827.308 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.06943  69.401596 77.05169  77.81181  73.9082   77.93284  78.70613\n",
      " 92.44365  73.358925 75.93392 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.49353  26.203762 31.440928 28.604605 31.042517 30.601765 24.950521\n",
      " 26.561306 35.168377 30.832409], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.85135 338.86264 400.75528 409.1014  392.6941  388.98718 418.64606\n",
      " 401.31406 409.4673  483.96942], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1261.8065   968.0257  1009.00476 1005.42786  979.3623  1011.11316\n",
      " 1041.9437  1027.9043   973.2493  1008.7829 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.39937 230.21127 227.5867  228.00471 227.49927 225.88345 231.62447\n",
      " 227.5407  236.34773 228.6792 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.6901  209.12772 227.08383 209.27359 209.10373 211.47205 209.3071\n",
      " 209.20181 209.15    210.17941], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[790.3923  681.43665 689.30164 803.4198  682.429   685.2814  680.97253\n",
      " 682.02905 679.03326 670.1571 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.61172 284.8155  284.90106 284.78375 286.49384 284.68637 284.8727\n",
      " 297.18613 304.18646 287.73077], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.7999  769.79144 799.0087  769.7642  791.27844 787.1321  947.8538\n",
      " 794.14594 807.8916  804.51044], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2268.928  1860.6627 1851.0504 1862.8523 1859.1648 1855.6506 1872.8496\n",
      " 1909.7953 1853.1111 1827.949 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.056076 69.43678  77.04918  77.80174  73.928116 77.921295 78.680916\n",
      " 92.04622  73.38207  75.94026 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.380257 26.225971 31.415485 28.611874 31.025858 30.591644 24.9782\n",
      " 26.581598 35.03661  30.81919 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.87357 339.17593 400.41327 408.56183 392.56665 388.94403 417.88983\n",
      " 400.95834 408.91922 481.754  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1256.0344   968.25977 1008.8666  1005.3685   979.514   1010.91455\n",
      " 1041.0137  1027.2875   973.4458  1008.6509 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.39468 230.12129 227.5789  227.9851  227.49312 225.88753 231.48984\n",
      " 227.53378 236.1114  228.63766], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.66904 209.12515 226.79802 209.272   209.10257 211.36165 209.2946\n",
      " 209.19495 209.14978 210.16568], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[789.25323 681.5013  689.27673 802.11035 682.47046 685.2889  681.0498\n",
      " 682.079   679.1622  670.4613 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.6075  284.81848 284.903   284.7871  286.48004 284.68423 284.87494\n",
      " 297.02185 303.91302 287.56122], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.8236  769.96735 798.9772  769.9403  791.31323 787.1967  944.22363\n",
      " 794.1595  807.6303  804.3378 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2263.854  1860.6715 1851.2435 1862.8425 1859.1871 1855.7213 1872.7607\n",
      " 1909.3748 1853.2487 1828.5902], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.04277  69.47218  77.04664  77.7917   73.947975 77.909775 78.6558\n",
      " 91.65344  73.40517  75.946556], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.26791  26.248129 31.390148 28.619091 31.009253 30.581547 25.005886\n",
      " 26.601828 34.905987 30.806004], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.89563 339.48898 400.07312 408.02533 392.4397  388.90097 417.1386\n",
      " 400.60455 408.3744  479.55914], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1250.3225   968.49304 1008.7291  1005.3096   979.66504 1010.717\n",
      " 1040.089   1026.6741   973.64124 1008.51953], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.38998 230.03252 227.57117 227.96567 227.48691 225.89168 231.35722\n",
      " 227.5269  235.87859 228.59663], shape=(10,), dtype=float32)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor(\n",
      "[210.64827 209.1226  226.51558 209.27043 209.10141 211.2542  209.28252\n",
      " 209.18832 209.14957 210.15215], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[788.1225  681.56573 689.2521  800.8109  682.512   685.2965  681.1269\n",
      " 682.1287  679.29083 670.76587], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.60333 284.82147 284.90503 284.7906  286.4664  284.68256 284.87726\n",
      " 296.85925 303.64252 287.39716], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.8471  770.14307 798.9458  770.1161  791.34796 787.26105 940.63837\n",
      " 794.17285 807.37036 804.1662 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2258.8228 1860.6803 1851.4371 1862.8334 1859.2096 1855.7917 1872.6725\n",
      " 1908.9564 1853.3861 1829.232 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.02948  69.5078   77.04408  77.78166  73.967735 77.898285 78.63078\n",
      " 91.26529  73.4282   75.95279 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.156487 26.270239 31.364933 28.626257 30.99271  30.571468 25.033579\n",
      " 26.622005 34.7765   30.792852], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.9175  339.80176 399.7347  407.49207 392.3133  388.858   416.39233\n",
      " 400.25262 407.83282 477.38467], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1244.6705   968.7259  1008.5919  1005.2507   979.8154  1010.51984\n",
      " 1039.17    1026.0641   973.8361  1008.38855], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.38533 229.94502 227.56343 227.94633 227.48079 225.89584 231.22665\n",
      " 227.52005 235.64922 228.556  ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.62769 209.12021 226.23636 209.26883 209.1003  211.14978 209.2709\n",
      " 209.18196 209.14932 210.13875], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[787.      681.63    689.2274  799.5211  682.55334 685.3041  681.20374\n",
      " 682.17847 679.41907 671.07074], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[285.59915 284.82452 284.90704 284.7941  286.45282 284.6814  284.87958\n",
      " 296.69836 303.37488 287.23843], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[792.8703  770.31854 798.9144  770.29175 791.38245 787.3252  937.09753\n",
      " 794.18604 807.1121  803.9955 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[2253.8335 1860.6891 1851.6293 1862.8242 1859.2317 1855.862  1872.5852\n",
      " 1908.5406 1853.5231 1829.8737], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[78.016235 69.54363  77.0415   77.771645 73.98746  77.886826 78.605865\n",
      " 90.881714 73.45115  75.95897 ], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[34.045982 26.292301 31.339819 28.633371 30.976215 30.561405 25.061268\n",
      " 26.642126 34.648144 30.779736], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[381.9392  340.11432 399.39804 406.96198 392.18738 388.8152  415.65097\n",
      " 399.90253 407.2945  475.23047], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[1239.0784   968.9575  1008.45526 1005.1918   979.96545 1010.3237\n",
      " 1038.2563  1025.4573   974.0304  1008.25793], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[227.38066 229.85873 227.55579 227.92722 227.47466 225.90007 231.09811\n",
      " 227.51321 235.42337 228.51582], shape=(10,), dtype=float32)\n",
      "tf.Tensor(\n",
      "[210.60738 209.11784 225.96045 209.2673  209.09924 211.04826 209.25957\n",
      " 209.17583 209.14912 210.12549], shape=(10,), dtype=float32)\n",
      "final epoch: train loss 559.47876 test loss 517.0827\n",
      "weight: [[-0.38668415]\n",
      " [ 0.3557009 ]\n",
      " [-0.42790684]] \n",
      "bias: [0.23983814]\n"
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    "fit_and_plot(poly_features[:n_train, :], poly_features[n_train:, :],\n",
    "             labels[:n_train], labels[n_train:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.11.4.4. 线性函数拟合（欠拟合）¶\n",
    "我们再试试线性函数拟合。很明显，该模型的训练误差在迭代早期下降后便很难继续降低。在完成最后一次迭代周期后，训练误差依旧很高。线性模型在非线性模型（如三阶多项式函数）生成的数据集上容易欠拟合。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
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   "outputs": [
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      "tf.Tensor([1446.4863 1433.7227], shape=(2,), dtype=float32)\n",
      "tf.Tensor([1445.8007 1433.689 ], shape=(2,), dtype=float32)\n",
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      "tf.Tensor([1440.3359 1433.4198], shape=(2,), dtype=float32)\n",
      "final epoch: train loss 1436.5208 test loss 527.09924\n",
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      " [-1.2402399 ]\n",
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